Method For Predicting Therapy Responsiveness In Basal Like Tumors

ABSTRACT

The present invention is related to a method for predicting a clinical response of a patient suffering from or at risk of developing a neoplastic disease towards at least one given mode of treatment, said method comprising the steps of:
         a) obtaining a biological sample from said patient;   b) determining, on a non protein basis, the expression level of at least one gene of interest, said gene being correlated with the Estrogen receptor (ESR) status in the said sample,   c) comparing the pattern of expression levels determined in (b) with one or several reference pattern(s) of expression levels; and   d) predicting therapeutic success for said given mode of treatment in said patient from the outcome of the comparison in step (c).

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application is a continuation of U.S. application Ser. No. 12/745,668, filed Dec. 21, 2010, which is a U.S. national phase application of International Application No. PCT/EP2008/065040, which was filed Nov. 6, 2008, and which claims the benefit of priority to U.S. Provisional Application No. 60/991,391, filed on Nov. 30, 2007. The content of these earlier filed applications is hereby incorporated herein by reference.

SEQUENCE LISTING

The Sequence Listing submitted herewith as a text filed named “13318_0032U3_Sequence_Listing.txt,” created on Mar. 2, 2018, and having a size of 8,192 bytes is hereby incorporated by reference pursuant to 37 C.F.R. § 1.52(e) (5).

FIELD OF THE INVENTION

The present invention relates to methods for prediction of the therapeutic success of cancer therapy.

BACKGROUND OF THE INVENTION

In some neoplastic diseases, particularly gynaecological cancers like breast cancer, the response to neoadjuvant chemotherapy is comparatively low, with only about 20% of patients achieving pathological complete remission (pCR) with no tumor cells left in the breast or lymph nodes; the latter being the strongest prognostic factor for prolonged survival due to treatment benefit to date.

However, a substantial number of patients suffer severe side effects (ADRs) from highly toxic drug combinations (e.g. alopecia due to inclusion of taxanes) without additional benefit. In addition, there is a burden on national health systems due to the high cost of some therapies in this regime, especially if the chemotoxic treatments are combined with new tareted treatment options (e.g. Herceptin®, Lapatinib® and Avastin®). Moreover the new treatment options are related with some severe, probably life threatening side effects (e.g. cardiac toxicities upon combinatorial treatment with Herceptin®, gastrointestinal perforation upon combinatorial treatment with Avastin).

A better characterization of the respective tumors would thus allow a better selection of the most promising therapy in a given breast cancer patient, in order to avoid unnecessary side effects due to neoadjuvant chemotherapy in those patients which do no not draw any benefit from such therapy anyway.

Some neoplastic diseases, particularly gynaecological cancers like breast cancer (BC), are characterized the fact that approximately 80% of them are estrogen receptor positive as characterized by standard immunohistochemistry, i.e. the exhibit estrogen receptors. However, it turned out that only a fraction of these tumors are dependent on hormone ligands (i.e. estrogen) for activation of Estrogen receptors (ESR) and sustained growth of the tumor tissue.

The estrogen receptor is a member of the nuclear hormone family of intracellular receptors which is activated by the hormone 17-β-estradiol (estrogen). The main function of the estrogen receptor is that of a DNA binding transcription factor which regulates gene expression. In addition a subfraction of estrogen receptor is able to interact with receptor tyrosine kinases (e.g. Her-2/neu) on the membrane which is critical for development of resistance towards cancer therapeutics.

Estrogen and the ESRs have also been implicated in breast cancer, ovarian cancer, colon cancer, prostate cancer and endometrial cancer. Advanced colon cancer is associated with a loss of ERβ (also termed ESR2), the predominant ESR in colon tissue, and colon cancer is treated with ERβ specific agonists in some cases.

As stated above, Estrogen receptors are overexpressed on the protein level in around 80% of breast cancer cases, referred to as “ESR positive”. Two hypotheses have been proposed to explain why this causes tumorigenesis. One stipulates that binding of estrogen to the ESR stimulates proliferation of mammary cells, with the resulting increase in cell division and DNA replication leading to mutations. The other one states that estrogen metabolism produces genotoxic waste.

The result of both processes is disruption of cell cycle, apoptosis and DNA repair and therefore tumor formation or growth.

Different versions of the ESR1 (also termed ERα), gene have been identified (with single-nucleotide polymorphisms) and are associated with different risks of developing breast cancer.

It has turned out that, typically, ESR-positive tumors demonstrate only poor responses on neoadjuvant chemotherapy, with about 10% pathological complete remission (pCR) reported.

However, ESR-positive tumors may profit from a treatment with Tamoxifen, an estrogen-receptor antagonist used as an adjuvant hormonal treatment. Another selective estrogen receptor modulator, raloxifene, has been used as a preventative chemotherapy for women judged to have a high risk of developing breast cancer. Another anti-estrogen, ICI 182,780 (Faslodex) which acts as a complete antagonist also promotes degradation of the estrogen receptor.

Other anti estrogen drugs are Anastrozole (Arimidex®), a drug which prevents the conversion of adrenal gland androgen hormones to estrogen, Exemestane (Aromasin®) and Letrozole (Ferrara®), which are inhibitors for the enzyme aromatase which is involved in the production of estrogen, and Megestrol acetate (Megace®) which is a progesteron agonist acting through competitive inhibition.

One current standard for diagnosis of early breast cancer is the determination of ESR1 by immunohistochemistry (IHC) using subsequent scoring systems. These assays are based on Protein-level measurements exhibiting limited quantitative performance and comparatively high inter- and intra-assay variabilities. Moreover, the final assessment is essentially subjective and is known to show substantial inter-operator (i.e. inter-pathologist) variance (Faneyte et al., 2003).

In this context, it has been shown that as few as 1 to 5% of ESR1 positive tumor cells within a given tumor are sufficient to specify this tumor as being potentially responsive to endocrine treatment. This is somewhat surprising as one would rather think that the 95% to 99% ESR1 protein negative tumor cells should not be dependent on estrogen and thereby not be responsive to endocrine treatment as described above. Conversely, this already shows the limitations of the protein determination of estrogen receptors as being insufficient to describe estrogen receptor dependent tumors. Clinically the 95% to 99% of estrogen receptor negative tumor cells have a high potential to be hormone dependent. Moreover, the determination of estrogen receptor status based on immunohistochemistry is highly subjective and varies between different labs (approximately 70% concordance). In view, of the marginal protein expression level of estrogen receptor being necessary to qualify for endocrine treatment this is critical.

Moreover, there are apparent differences between ESR1 positive tumors, which clearly separate the growth characteristics and dependency on solely estrogen. For example, it has been shown that a significant fraction of estrogen receptor coexpress progesteron receptor and/or the receptor tyrosine kinase Her-2/neu. This raises e.g. the possibility of estrogen independent growth capabilities via progesterone or EGFR family ligands.

Nevertheless, Estrogen receptor positive tumors do have a comparably good prognosis, while Estrogen receptor negative tumors as determined by IHC have a particularly bad prognosis.

It has yet been reported that about 20% of breast cancer cases are independent of estrogen, and are thus resistant against anti estrogen treatments (Ring et al., 2004).

These tumors, however, seem to demonstrate a better response towards chemotherapy, with about 20% pathological complete remission (pCR) reported. In addition, if Her-2/neu positive, these tumors may additionally have benefit from anti-Her-2/neu regimen such as Herceptin™ or Tykerb™. Apparently, bad prognosis tumors particularly bear the potential of benefit from combined antibody and chemotherapeutic regimen.

Still, not at least in view of the new therapeutic options, the worst prognosis among the breast cancer subgroups do have estrogen receptor negative, progesterone receptor negative and Her-2/neu receptor negative breast cancer, which are also the so called “basal like tumors” as originally defined by multiparametric gene array analysis by unsupervised cluster analysis (Sorlie et al., 2001)

However, the precise definition of the so called “basal like tumors” has been defined by fresh tissue RNA analysis using multigene arrays, and the definition of the “basal like tumors” by immunohistochemistry in fixed tissue routine samples is far from being adaequate. Moreover, the “basal like tumors” itself seem to be clinically heterogenous and do contain two very different subtypes, one of which seems to have a particularly good response to chemotherapy.

A proper differentiation between these two “basal like” tumor subclasses would help to apply or develop patient or tumor specific therapies, in order to reduce side effects and improve tumor remission rates.

Moreover, new targets for newly available targeted drugs, or drugs yet to be developed, could thus be determined.

It is obvious that current methods do not suffice to characterize a high risk or low risk “basal like tumor” in a reliable and reproducible way by immunohistochemically determining it as ESR-negative, PR-negative and Her-2/neu negative.

Definitions

The term “determining the expression level of a gene/protein on a non protein basis” relates to methods which are not restricted to the secondary gene translation products, i.e proteins, but on other levels of the gene expression, like the mRNA, premRNA and genomic DNA structures.

The terms “positive receptor status” and “negative receptor status” relate to the presence or absence of a given receptor, e.g. ESR, PGR or Her-2/neu, in a tissue sample. Usually, the respective status is being determined by IHC.

The term “chemotherapy” relates to a drug therapy which affects cell growth and cell division, i.e. which acts as a cytostatic, or which induces cell death (apoptosis). Due to their uncontrolled growth and division, cancer cells are supposed to be more affected by chemotherapy than normal cells.

The term “neoadjuvant therapy” relates to a preoperative therapy regimen consisting of a panel of hormonal, chemotherapeutic and/or antibody agents, which is aimed to shrink the primary tumour, thereby rendering local therapy (surgery or radiotherapy) less destructive or more effective, enabling breast conserving surgery and evaluation of responsiveness of tumor sensitivity towards specific agents in vivo.

The term “targeted therapy” refers to a therapy which aims at recognizing particular target molecules, which may play a role in tumor genesis or proliferation, or cell repair, for example. Such recognition may for example lead to a binding of the said target molecule, which may either enhance or decrease its activity. Drugs used for such therapy comprise, among others, antibodies, particularly monoclonal antibodies, and small molecular drugs.

Potential targets are, for example, the EGFR receptor (which plays an important role in angiogenesis), the VEGFA ligand (likewise important for angiogenesis) or PARP1 (important for cell repair, as its inhibition makes tumors characterized by oncogene defects more susceptive to chemotherapy).

The term “prediction”, as used herein, relates to an individual assessment of the malignancy of a tumor, or to the expected survival rate (DFS, disease free survival; OAS, overall survival; DSS, Disease specific survival) of a patient, if the tumor is treated with a given therapy. In contrast thereto, the term “prognosis” relates to an individual assessment of the malignancy of a tumor, or to the expected survival rate (DFS, disease free survival; OAS, overall survival; DSS, Disease specific survival) of a patient, unaffected and/or independent of the tumor treatment.

The term “response marker” relates to a marker which can be used to predict the clinical response and/or clinical outcome of a patient towards a given treatment.

The term “neoplastic lesion” or “neoplastic disease” or “neoplasia” refers to a cancerous tissue this includes carcinomas, (e.g., carcinoma in situ, invasive carcinoma, metastatic carcinoma) and pre-malignant conditions, neomorphic changes independent of their histological origin (e.g. ductal, lobular, medullary, mixed origin). The term “cancer” as used herein includes carcinomas, (e.g., carcinoma in situ, invasive carcinoma, metastatic carcinoma) and pre-malignant conditions, neomorphic changes independent of their histological origin. The term “cancer” is not limited to any stage, grade, histomorphological feature, invasiveness, agressivity or malignancy of an affected tissue or cell aggregation. In particular stage 0 cancer, stage I cancer, stage II cancer, stage III cancer, stage IV cancer, grade I cancer, grade II cancer, grade III cancer, malignant cancer, primary carcinomas, and all other types of cancers, malignancies and transformations associated with the lung, ovar, cervix, endometrium, esophagus, stomach, pancreas, prostate, head and neck, renal cell, liver, colorectal or breast cancer are included. Particularly types of adenocarcinoma are included, as well as all carcinomas of unknown primary (cup-syndromes).

The terms “neoplastic lesion” or “neoplastic disease” or “neoplasia” or “cancer” are not limited to any tissue or cell type they also include primary, secondary or metastatic lesions of cancer patients, and also comprises lymph nodes affected by cancer cells or minimal residual disease cells either locally deposited (e.g. bone marrow, liver, kidney) or freely floating throughout the patient's body.

The term “neoplastic cells” refer to abnormal cells that grow by cellular proliferation more rapidly than normal. As such, neoplastic cells of the invention may be cells of a benign neoplasm or may be cells of a malignant neoplasm.

Furthermore, the term “characterizing the state of a neoplastic disease” is related to, but not limited to, measurements and assessment of one or more of the following conditions: Type of tumor, histomorphological appearance, dependence on external signal (e.g. hormones, growth factors), invasiveness, motility, state by TNM (2) or similar, agressivity, malignancy, metastatic potential, and responsiveness to a given therapy.

The term “Her-2/neu” relates to a gene encoding for a cell signalling protein. Synonyms for this gene are “ErbB” or “ERBB”. The three terms are being used interchangeably in this specification.

The terms “biological sample” or “clinical sample”, as used herein, refer to a sample obtained from a patient. The sample may be of any biological tissue or fluid. Such samples include, but are not limited to, sputum, blood, serum, plasma, blood cells (e.g., white cells), circulating cells (e.g. stem cells or endothelial cells in the blood, tissue, core or fine needle biopsy samples, cell-containing body fluids, free floating nucleic acids, urine, stool, peritoneal fluid, and pleural fluid, liquor cerebrospinalis, tear fluid, or cells there from. Biological samples may also include sections of tissues such as frozen or fixed sections taken for histological purposes or microdissected cells or extracellular parts thereof. A biological sample to be analyzed is tissue material from a neoplastic lesion taken by aspiration or punctuation, excision or by any other surgical method leading to biopsy or resected cellular material. Such a biological sample may comprise cells obtained from a patient. The cells may be found in a cell “smear” collected, for example, by a nipple aspiration, ductal lavarge, fine needle biopsy or from provoked or spontaneous nipple discharge. In another embodiment, the sample is a body fluid. Such fluids include, for example, blood fluids, serum, plasma, lymph, ascitic fluids, gynecological fluids, or urine but not limited to these fluids.

The term “therapy modality”, “therapy mode”, “regimen” or “chemo regimen” as well as “therapy regimen” refers to a timely sequential or simultaneous administration of anti-tumor, and/or anti vascular, and/or anti stroma, and/or immune stimulating, and/or blood cell proliferative agents, and/or radiation therapy, and/or hyperthermia, and/or hypothermia for cancer therapy. The administration of these can be performed in an adjuvant and/or neoadjuvant mode. The composition of such “protocol” may vary in the dose of each of the single agents, timeframe of application and frequency of administration within a defined therapy window. Currently various combinations of various drugs and/or physical methods, and various schedules are under investigation.

By “array” or “matrix” an arrangement of addressable locations or “addresses” on a device is meant. The locations can be arranged in two dimensional arrays, three dimensional arrays, or other matrix formats. The number of locations can range from several to at least hundreds of thousands. Most importantly, each location represents a totally independent reaction site. Arrays include but are not limited to nucleic acid arrays, protein arrays and antibody arrays. A “nucleic acid array” refers to an array containing nucleic acid probes, such as oligonucleotides, nucleotide analogues, polynucleotides, polymers of nucleotide analogues, morpholinos or larger portions of genes. The nucleic acid and/or analogue on the array is preferably single stranded. Arrays wherein the probes are oligonucleotides are referred to as “oligonucleotide arrays” or “oligonucleotide chips.” A “microarray,” herein also refers to a “biochip” or “biological chip”, an array of regions having a density of discrete regions of at least about 100/cm², and preferably at least about 1000/cm². The regions in a microarray have typical dimensions, e.g., diameters, in the range of between about 10-250 μm, and are separated from other regions in the array by about the same distance. A “protein array” refers to an array containing polypeptide probes or protein probes which can be in native form or denatured. An “antibody array” refers to an array containing antibodies which include but are not limited to monoclonal antibodies (e.g. from a mouse), chimeric antibodies, humanized antibodies or phage antibodies and single chain antibodies as well as fragments from antibodies.

The term “small molecule”, as used herein, is meant to refer to a compound which has a molecular weight of less than about 5 kD and most preferably less than about 4 kD. Small molecules can be nucleic acids, peptides, polypeptides, peptidomimetics, carbohydrates, lipids or other organic (carbon-containing) or inorganic molecules. Many pharmaceutical companies have extensive libraries of chemical and/or biological mixtures, often fungal, bacterial, or algal extracts, which can be screened with any of the assays of the invention to identify compounds that modulate a bioactivity.

The terms “modulated” or “modulation” or “regulated” or “regulation” and “differentially regulated” as used herein refer to both upregulation [i.e., activation or stimulation, e.g., by agonizing or potentiating] and down regulation [i.e., inhibition or suppression, e.g., by antagonizing, decreasing or inhibiting].

The term “transcriptome” relates to the set of all messenger RNA (mRNA) molecules, or “transcripts”, produced in one or a population of cells. Importantly, this term includes also non-translated RNAs such as “micro RNA's”, which affect cellular characteristics because of gene regulation functions (silencing or activation or stabilization or degradation of other genes and transcripts). The term can be applied to the total set of transcripts in a given organism, or to the specific subset of transcripts present in a particular cell type. Unlike the genome, which is roughly fixed for a given cell line (excluding mutations), the transcriptome can vary with external environmental conditions. Because it includes all RNA transcripts in the cell, the transcriptome reflects the genes that are being actively expressed at any given time, with the exception of mRNA degradation phenomena such as transcriptional attenuation. It also includes posttranscriptional events such as alternative splicing. The discipline of transcriptomics examines the expression level of mRNAs in a given cell population, often using high-throughput techniques based on DNA microarray technology.

The term “expression levels” refers, e.g., to a determined level of gene expression. The term “pattern of expression levels” refers to a determined level of gene expression compared either to a reference gene (e.g. housekeeper or inversely regulated genes) or to a computed average expression value (e.g. in DNA-chip analyses). A pattern is not limited to the comparison of two genes but is more related to multiple comparisons of genes to reference genes or samples. A certain “pattern of expression levels” may also result and be determined by comparison and measurement of several genes disclosed hereafter and display the relative abundance of these transcripts to each other.

Alternatively, a differentially expressed gene disclosed herein may be used in methods for identifying reagents and compounds and uses of these reagents and compounds for the treatment of cancer as well as methods of treatment. The differential regulation of the gene is not limited to a specific cancer cell type or clone, but rather displays the interplay of cancer cells, muscle cells, stromal cells, connective tissue cells, other epithelial cells, endothelial cells of blood vessels as well as cells of the immune system (e.g. lymphocytes, macrophages, killer cells).

A “reference pattern of expression levels”, within the meaning of the invention shall be understood as being any pattern of expression levels that can be used for the comparison to another pattern of expression levels. In a preferred embodiment of the invention, a reference pattern of expression levels is, e.g., an average pattern of expression levels observed in a group of healthy or diseased individuals, serving as a reference group.

“Primer pairs” and “probes”, within the meaning of the invention, shall have the ordinary meaning of this term which is well known to the person skilled in the art of molecular biology. In a preferred embodiment of the invention “primer pairs” and “probes”, shall be understood as being polynucleotide molecules having a sequence identical, complementary, homologous, or homologous to the complement of regions of a target polynucleotide which is to be detected or quantified. In yet another embodiment nucleotide analogues and/or morpholinos are also comprised for usage as primers and/or probes.

“Individually labeled probes”, within the meaning of the invention, shall be understood as being molecular probes comprising a polynucleotide, oligonucleotide or nucleotide analogue and a label, helpful in the detection or quantification of the probe. Preferred labels are fluorescent molecules, luminescent molecules, radioactive molecules, enzymatic molecules and/or quenching molecules.

“Arrayed probes”, within the meaning of the invention, shall be understood as being a collection of immobilized probes, preferably in an orderly arrangement. In a preferred embodiment of the invention, the individual “arrayed probes” can be identified by their respective position on the solid support, e.g., on a “chip”.

The phrase “tumor response”, “therapeutic success”, or “response to therapy” refers, in the adjuvant chemotherapeutic setting to the observation of a defined tumor free or recurrence free survival time (e.g. 2 years, 4 years, 5 years, 10 years). This time period of disease free survival may vary among the different tumor entities but is sufficiently longer than the average time period in which most of the recurrences appear. In a neo-adjuvant therapy modality, response may be monitored by measurement of tumor shrinkage and regression due to apoptosis and necrosis of the tumor mass.

The term “recurrence” or “recurrent disease” includes distant metastasis that can appear even many years after the initial diagnosis and therapy of a tumor, or local events such as infiltration of tumor cells into regional lymph nodes, or occurrence of tumor cells at the same site and organ of origin within an appropriate time.

“Prediction of recurrence” or “prediction of therapeutic success” does refer to the methods described in this invention. Wherein a tumor specimen is analyzed for it's gene expression and furthermore classified based on correlation of the expression pattern to known ones from reference samples. This classification may either result in the statement that such given tumor will develop recurrence and therefore is considered as a “non responding” tumor to the given therapy, or may result in a classification as a tumor with a prolonged disease free post therapy time.

“Biological activity” or “bioactivity” or “activity” or “biological function”, which are used interchangeably, herein mean an effector or antigenic function that is directly or indirectly exerted by a polypeptide (whether in its native or denatured conformation), or by any fragment thereof in vivo or in vitro. Biological activities include but are not limited to binding to polypeptides, binding to other proteins or molecules, enzymatic activity, signal transduction, activity as a DNA binding protein, as a transcription regulator, ability to bind damaged DNA, etc. A bioactivity can be modulated by directly affecting the subject polypeptide. Alternatively, a bioactivity can be altered by modulating the level of the polypeptide, such as by modulating expression of the corresponding gene.

The term “marker” or “biomarker” refers to a biological molecule, e.g., a nucleic acid, peptide, protein, hormone, etc., whose presence or concentration can be detected and correlated with a known condition, such as a disease state.

The term “ligand”, as used herein, relates to a molecule that is able to bind to and form a complex with a biomolecule to serve a biological purpose. In a narrower sense, it is an effector molecule binding to a site on a target protein, by intermolecular forces such as ionic bonds, hydrogen bonds and Van der Waals forces. The docking (association) is usually reversible (dissociation). Actual irreversible covalent binding between a ligand and its target molecule is rare in biological systems. Ligand binding to receptors often alters the chemical conformation, i.e. the three dimensional shape of the receptor protein. The conformational state of a receptor protein determines the functional state of a receptor. The tendency or strength of binding is called affinity. Ligands include substrates, inhibitors, activators, and neurotransmitters.

The term “agonist”, as used herein, relates to a substance that binds to a specific receptor and triggers a response in the cell. It mimics the action of an endogenous ligand that binds to the same receptor.

The term “receptor”, as used herein, relates to a protein on the cell membrane or within the cytoplasm or cell nucleus that binds to a specific molecule (a ligand), such as a neurotransmitter, hormone, or other substance, and initiates the cellular response to the ligand. Ligand-induced changes in the behavior of receptor proteins result in physiological changes that constitute the biological actions of the ligands.

The term “signalling pathway” is related to any intra- or intercellular process by which cells converts one kind of signal or stimulus into another, most often involving ordered sequences of biochemical reactions out- and inside the cell, that are carried out by enzymes and linked through hormones and growth factors (intercellular), as well as second messengers (intracellular), the latter resulting in what is thought of as a “second messenger pathway”. In many signalling pathways, the number of proteins and other molecules participating in these events increases as the process emanates from the initial stimulus, resulting in a “signal cascade” and often results in a relatively small stimulus eliciting a large response.

The term “marker gene,” as used herein, refers to a differentially expressed gene whose expression pattern may be utilized as part of a predictive, prognostic or diagnostic process in healthy conditions, premalignant disease status, malignant neoplasia or cancer evaluation, or which, alternatively, may be used in methods for identifying compounds useful for the treatment or prevention of malignant neoplasia and head and neck, colon or breast cancer in particular. A marker gene may also have the characteristics of a target gene.

“Target gene”, as used herein, refers to a differentially expressed gene involved in cancer or pre-cancerous lesions, e.g., lung, head and neck, colon, ovarian or breast cancer in a manner in which modulation of the level of the target gene expression or of the target gene product activity may act to ameliorate symptoms of malignant neoplasia and lung, liver, endometrium, ovarian, cervix, esophagus, stomach, pancreas, prostate, head and neck, renal cell, colorectal or breast cancer in particular. A target gene may also have the characteristics of a marker gene.

The term “expression level”, as used herein, relates to each step within the process by which a gene's DNA sequence is converted into functional protein (i.e. ligands) via RNA intermediates and particularly to the amount of said conversion.

The term “hybridization based method”, as used herein, refers to methods imparting a process of combining complementary, single-stranded nucleic acids or nucleotide analogues into a single double stranded molecule. Nucleotides or nucleotide analogues will bind to their complement under normal conditions, so two perfectly complementary strands will bind to each other readily. In bioanalytics, very often labeled, single stranded probes are in order to find complementary target sequences. If such sequences exist in the sample, the probes will hybridize to said sequences which can then be detected due to the label. Other hybridization based methods comprise microarray and/or biochip methods. Therein, probes are immobilized on a solid phase, which is then exposed to a sample. If complementary nucleic acids exist in the sample, these will hybridize to the probes and can thus be detected. These approaches are also known as “array based methods”. Yet another hybridization based method is PCR, which is described below. When it comes to the determination of expression levels, hybridization based methods may for example be used to determine the amount of mRNA for a given gene.

“Serial analysis of gene expression” (SAGE) is a method for comprehensive analysis of gene expression patterns, which is based on the facts that (i) a short sequence tag (10-14 bp) contains sufficient information to uniquely identify a transcript provided that that the tag is obtained from a unique position within each transcript; (ii) sequence tags can be linked together to from long serial molecules that can be cloned and sequenced; and (iii) quantitation of the number of times a particular tag is observed provides the expression.

The term “a PCR based method” as used herein refers to methods comprising a polymerase chain reaction (PCR). This is a method of exponentially amplifying nucleic acids, e.g. DNA by enzymatic replication in vitro. As PCR is an in vitro technique, it can be performed without restrictions on the form of DNA, and it can be extensively modified to perform a wide array of genetic manipulations. When it comes to the determination of expression levels, a PCR based method may for example be used to detect the presence of a given mRNA by (1) reverse transcription of the complete mRNA pool (the so called transcriptome) into cDNA with help of a reverse transcriptase enzyme, and (2) detecting the presence of a given cDNA with help of respective primers. This approach is commonly known as reverse transcriptase PCR (rtPCR).

Moreover, PCR-based methods comprise e.g. real time PCR, and, particularly suited for the analysis of expression levels, kinetic or quantitative PCR (qPCR).

The term “Quantitative real-time PCR” (qPCR)” refers to any type of a PCR method which allows the quantification of the template in a sample. Quantitative real-time PCR comprise different techniques of performance or product detection as for example the TaqMan technique or the LightCycler technique. The TaqMan technique, for examples, uses a dual-labelled fluorogenic probe. The TaqMan real-time PCR measures accumulation of a product via the fluorophore during the exponential stages of the PCR, rather than at the end point as in conventional PCR. The exponential increase of the product is used to determine the threshold cycle, CT, i.e. the number of PCR cycles at which a significant exponential increase in fluorescence is detected, and which is directly correlated with the number of copies of DNA template present in the reaction. The set up of the reaction is very similar to a conventional PCR, but is carried out in a real-time thermal cycler that allows measurement of fluorescent molecules in the PCR tubes. Different from regular PCR, in TaqMan real-time PCR a probe is added to the reaction, i.e., a single-stranded oligonucleotide complementary to a segment of 20-60 nucleotides within the DNA template and located between the two primers. A fluorescent reporter or fluorophore (e.g., 6-carboxyfluorescein, acronym: FAM, or tetrachlorofluorescin, acronym: TET) and quencher (e.g., tetramethylrhodamine, acronym: TAMRA, of dihydrocyclopyrroloindole tripeptide “minor groove binder”, acronym: MGB) are covalently attached to the 5′ and 3′ ends of the probe, respectively[2]. The close proximity between fluorophore and quencher attached to the probe inhibits fluorescence from the fluorophore. During PCR, as DNA synthesis commences, the 5′ to 3′ exonuclease activity of the Taq polymerase degrades that proportion of the probe that has annealed to the template (Hence its name: Taq polymerase+PacMan). Degradation of the probe releases the fluorophore from it and breaks the close proximity to the quencher, thus relieving the quenching effect and allowing fluorescence of the fluorophore. Hence, fluorescence detected in the real-time PCR thermal cycler is directly proportional to the fluorophore released and the amount of DNA template present in the PCR.

The term “planar waveguide” (PWG) relates to detection chips and chambers for performing multiplex PCR assays, as for example disclosed in WO2007059423, which has been filed by the applicant of the present invention and which is incorporated herein by reference. Such planar waveguides may be used in methods of performing a multiplex polymerase chain reaction (PCR) assay with a single fluorogenic dye. Compared to other biochips or microarrays they have a far better sensitivity and do thus put aside the need of an additional amplification step.

The term “determining the protein level”, as used herein, refers to methods which allow the quantitative and/or qualitative determination of one or more proteins in a sample. These methods include, among others, protein purification, including ultracentrifugation, precipitation and chromatography, as well as protein analysis and determination, including the use protein microarrays, two-hybrid screening, blotting methods including western blot, one- and two dimensional gel electrophoresis, isoelectric focusing as well as methods being based mass spectrometry like MALDI-TOF and the like.

The term “method based on the electrochemical detection of molecules” relates to methods which make use of an electrode system to which molecules, particularly biomolecules like proteins, nucleic acids, antigens, antibodies and the like, bind under creation of a detectable signal. Such methods are for example disclosed in WO0242759, WO0241992 and WO02097413 filed by the applicant of the present invention, the content of which is incorporated by reference herein. These detectors comprise a substrate with a planar surface which is formed, for example, by the crystallographic surface of a silicon chip, and electrical detectors which may adopt, for example, the shape of interdigital electrodes or a two dimensional electrode array. These electrodes carry probe molecules, e.g. nucleic acid probes, capable of binding specifically to target molecules, e.g. target nucleic acid molecules. The probe molecules are for example immobilized by a Thiol-Gold-binding. For this purpose, the probe is modified at its 5′- or 3′-end with a thiol group which binds to the electrode comprising a gold surface. These target nucleic acid molecules may carry, for example, an enzyme label, like horseradish peroxidise (HRP) or alkaline phosphatase. After the target molecules have bound to the probes, a substrate is then added (e.g., α-naphthyl phosphate or 3,3′5,5′-tetramethylbenzidine which is converted by said enzyme, particularly in a redox-reaction. The product of said reaction, or a current generated in said reaction due to an exchange of electrons, can then be detected with help of the electrical detector in a site specific manner.

The term “anamnesis” relates to patient data gained by a physician or other healthcare professional by asking specific questions, either of the patient or of other people who know the person and can give suitable information (in this case, it is sometimes called heteroanamnesis), with the aim of obtaining information useful in formulating a diagnosis and providing medical care to the patient. This kind of information is called the symptoms, in contrast with clinical signs, which are ascertained by direct examination.

The term “etiopathology” relates to the course of a disease, that is its duration, its clinical symptoms, and its outcome.

The term “detection of a ligand and/or receptor” as used herein means both the qualitative detection of the presence of the respective gene as well as the quantitative detect detection of the expression level of the respective gene, e.g. by quantitative reverse transcriptase PCR.

The term “nucleic acid molecule” is intended to indicate any single- or double stranded nucleic acid molecule comprising DNA (cDNA and/or genomic DNA), RNA (preferably mRNA), PNA, LNA and/or Morpholino.

The term “stringent conditions” relates to conditions under which a probe will preferably hybridize to its target subsequence and much less to other sequences. Stringent conditions are sequence-dependent and will be different in different circumstances. Longer sequences hybridize specifically at higher temperatures. Generally, stringent conditions are selected to be about 5° C. lower than the thermal melting point (Tm) for the specific sequence at a defined ionic strength and pH. The Tm is the temperature (under defined ionic strength, pH and nucleic acid concentration) at which 50% of the probes complementary to the target sequence hybridize to the target sequence at equilibrium. (As the target sequences are generally present in excess, at Tm, 50% of the probes are occupied at equilibrium). Typically, stringent conditions will be those in which the salt concentration is less than about 1.0 M Na ion, typically about 0.01 to 1.0 M Na ion (or other salts) at pH 7.0 to 8.3 and the temperature is at least about 30° C. for short probes (e.g. 10 to 50 nucleotides) and at least about 60° C. for longer probes. Stringent conditions may also be achieved with the addition of destabilizing agents, such as formamide and the like.

The term “fragment of the nucleic acid molecule” is intended to indicate a nucleic acid comprising a subset of a nucleic acid molecule according to one of the claimed sequences. The same is applicable to the term “fraction of the nucleic acid molecule”.

The term “variant of the nucleic acid molecule” refers herein to a nucleic acid molecule which is substantially similar in structure and biological activity to a nucleic acid molecule according to one of the claimed sequences.

The term “homologue of the nucleic acid molecule” refers to a nucleic acid molecule the sequence of which has one or more nucleotides added, deleted, substituted or otherwise chemically modified in comparison to a nucleic acid molecule according to one of the claimed sequences, provided always that the homologue retains substantially the same binding properties as the latter.

The term “derivative”, as used herein, refers to a nucleic acid molecule that has similar binding characteristics to a target nucleic acid sequence as a nucleic acid molecule according to one of the claimed sequences.

The term “sequence identity of at least X %” refers to a sequence identity as determined after a sequence alignment carried out with the family of BLAST algorithms as accessible on the respective Internet domain provided by NCBI.

OBJECT OF THE INVENTION

It is one object of the present invention to detect cancer subtypes which are characterized in that they are estrogen receptor negative, progesterone receptor negative and Her-2/neu receptor negative (“basal type tumors”), in order to provide chemotherapeutic and/or antibody based regimen specially suitable for these cancer types.

It is another object of the present invention to provide means to further differentiate between different basal type tumor subgroups.

It is another object of the present invention to identify basal type tumors having high probability to respond to chemotherapy regimen (“low risk basal type tumors”), and/or to identify basal type tumors that do not respond to chemotherapy (“high risk basal type tumors”) in order to identify target genes that might serve as more effective treatment alternatives.

It is another object of the present invention to offer a more robust and specific diagnostic assay system than conventional immunohistochemistry for clinical routine fixed tissue samples that better helps the physician to select individualized treatment modalities. In a more preferred embodiment the disclosed method can be used to select chemotherapeutic and/or antibody based regimen for breast cancers exhibiting reduced estrogen receptor expression on RNA and or/protein level.

It is another object of the present invention to detect new targets for newly available targeted drugs, or to determine drugs yet to be developed.

SUMMARY OF THE INVENTION

Before the invention is described in detail, it is to be understood that this invention is not limited to the particular component parts of the devices described or process steps of the methods described as such devices and methods may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limiting. It must be noted that, as used in the specification and the appended claims, the singular forms “a,” “an” and “the” include singular and/or plural referents unless the context clearly dictates otherwise. It is moreover to be understood that, in case parameter ranges are given which are delimited by numeric values, the ranges are deemed to include these limitation values.

According to the invention, a method is provided for predicting a clinical response of a patient suffering from or at risk of developing a neoplastic disease towards at least one given mode of treatment, said method comprising the steps of:

-   -   a) obtaining a biological sample from said patient;     -   b) determining, on a non-protein basis, the expression level of         at least one gene of interest, said gene being correlated with         the Estrogen receptor (ESR) status in the said sample,     -   c) comparing the pattern of expression levels determined in (b)         with one or several reference pattern(s) of expression levels;         and     -   d) predicting therapeutic success for said given mode of         treatment in said patient from the outcome of the comparison in         step (c).

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows results of an Affymetrix array analysis (HG U133A) in fresh tissue biopsies or RT-kPCR analysis in fixed tissue biopsies of high risk breast tumors.

FIG. 2 shows identification of the basa-like subtypes based on 2D hierarchial clustering.

FIG. 3 shows a Kaplan Meyer curve in which, for the different groups determined as above (see Example 3, the overall survival time (OAS) is plotted versus the respective percentage.

FIG. 4 shows a Kaplan Meyer curve in which, for the different groups determined as above (see Example 3, the overall survival time (OAS) is plotted versus the respective percentage.

Basically, a deviating expression level of either of the aformentioned genes can have different reasons, these being

-   -   gene amplification of an oncogene (frequently seen in Her-2/neu)     -   overexpression of the respective gene due to an altered         Methylation pattern, mutations     -   altered properties of a transcription factor, a promotor or         another factor which leads to an upregulation of the expression         level of the said agent.

In a preferred embodiment of the present invention, it is provided that the at least one gene of interest is correlated with a negative Estrogen receptor status.

The applicants have, in various studies, analyzed breast tumors with ESR1 negative and Her-2/neu negative status as determined with Immunochistochemistry (IHC) and/or Fluorescence In situ Hybridization (FISH). Core needle biopsy specimen of these tumors was analyzed on the DNA and RNA level by quantitative PCR, RT-PCR and array technologies.

During this process, the applicants have, surprisingly, identified a number of candidate genes which are correlated with, and are thus predictive for, subgroups of Estrogen receptor negative tumors (ESR−).

The following genes were identified to be useful for the discrimination of ESR1 positive tumors (IHC status 4, i.e. ESR status as determined with Immunohistochemistry) from ESR1 negative tumors (IHC status 0) by having high expression levels, high variance and fold change levels as identified in fresh tumor tissue.

TABLE 1 Genes that can be used to discriminate ESR1 positive tumors from ESR1 negative tumors Gene Map Locus RefSeq Symbol Location Link OMIM UniGene Transcript AKR7A3 chr1p35.1-p36.23 22977 608477 Hs.6980 NM_012067 ALCAM chr3q13.1 214 601662 Hs.150693 NM_001627 AR chrXq11.2-q12 367 313700 Hs.496240 NM_000044, NM_001011645 ASPN chr9q22 54829 608135 Hs.435655 NM_017680 BCL2 chr18q21.33|18q21.3 596 151430 Hs.150749 NM_000633, NM_000657 C6orf211 chr6q25.1 79624 Hs.15929 NM_024573 CA12 chr15q22 771 603263 Hs.210995 NM_001218, NM_206925 CCND1 chr11q13 595 168461 Hs.523852 NM_053056 CDC2 chr10q21.1 983 116940 Hs.334562 NM_001786, NM_033379 CEACAM6 chr19q13.2 4680 163980 Hs.466814 NM_002483 CELSR1 chr22q13.3 9620 604523 Hs.252387 NM_014246 CHI3L1 chr1q32.1 1116 601525 Hs.382202 NM_001276 COL4A5 chrXq22 1287 303630 Hs.369089 NM_000495, NM_033380, NM_033381 CPE chr4q32.3 1363 114855 Hs.75360 NM_001873 CRAT chr9q34.1 1384 600184 Hs.12068 NM_000755, NM_004003, NM_144782 CXCL9 chr4q21 601704 Hs.77367 CX3CR1 chr3p21|3p21.3 1524 601470 Hs.78913 NM_001337 CXCL10 chr4q21 3627 147310 Hs.413924 NM_001565 DNAJC12 chr10q22.1 56521 606060 Hs.260720 NM_021800, NM_201262 ERBB2/ chr17q11.2-q12| Her-2/neu 17q21.1 ERBB4 chr2q33.3-q34 2066 600543 Hs.390729 NM_005235 ESR1 chr6q25.1 2099 133430 Hs.208124 NM_000125 FBP1 chr9q22.3 2203 229700 Hs.494496 NM_000507 FLJ20152 chr5p15.1 54463 Hs.481704 NM_019000 FOS chr14q24.3 2353 164810 Hs.25647 NM_005252 FOXA1 chr14q12-q13 3169 602294 Hs.163484 NM_004496 GATA3 chr10p15 2625 131320 Hs.524134 NM_001002295, NM_002051 IGF2 chr11p15.5 3481 147470 Hs.523414 NM_001007139 ITPR1 chr3p26-p25 3708 147265 Hs.374613 NM_002222 JMJD2B chr19p13.3 23030 Hs.371013 NM_015015 KIAA0303 chr5q12.3 23227 Hs.133539 XM_291141 KIAA0882 chr4q31.21 23158 Hs.480819 NM_015130 KIF5C chr2q23.1 3800 604593 Hs.435557 XM_377774 KRT23 chr17q21.2 25984 606194 Hs.9029 NM_015515, NM_173213 KRT5 chr12q12-q13 3852 148040 Hs.433845 NM_000424 KRT6B chr12q12-q13 3854 148042 Hs.524438 NM_005555 MAPT chr17q21.1 4137 157140 Hs.101174 NM_005910, NM_016834, NM_016835, NM_016841 MLPH chr2q37.3 79083 606526 Hs.102406 NM_024101 MMP7 chr11q21-q22 4316 178990 Hs.2256 NM_002423 NAT1 chr8p23.1-p21.3 9 108345 Hs.155956 NM_000662 PHGDH chr1p12 26227 606879 Hs.487296 NM_006623 PROM1 chr4p15.32 8842 604365 Hs.479220 NM_006017 RARRES1 chr3q25.32 5918 605090 Hs.131269 NM_002888, NM_206963 RRM2 chr2p25-p24 6241 180390 Hs.226390 NM_001034 RRM2 chr2p25-p24 6241 180390 Hs.226390 NM_001034 S100A8 chr1q21 6279 123885 Hs.416073 NM_002964 SCNN1A chr12p13 6337 600228 Hs.130989 NM_001038 SCUBE2 chr11p15.3 57758 Hs.523468 NM_020974 SEMA3C chr7q21-q31 10512 602645 Hs.269109 NM_006379 SFRP1 chr8p12-p11.1 6422 604156 Hs.213424 NM_003012 SLC7A5 chr16q24.3 8140 600182 Hs.513797 NM_003486 SLC7A8 chr14q11.2 23428 604235 Hs.22891 NM_012244, NM_182728 SLPI chr20q12 6590 107285 Hs.517070 NM_003064 SOCS2 chr12q 8835 605117 Hs.485572 NM_003877 SOD2 chr6q25.3 6648 147460 Hs.487046 NM_000636 SPDEF chr6p21.3 25803 608144 Hs.485158 NM_012391 STC2 chr5q35.1 8614 603665 Hs.233160 NM_003714 TFF1 chr21q22.3 7031 113710 Hs.162807 NM_003225 TFF3 chr21q22.3 7033 600633 Hs.82961 NM_003226 TOP2A chr17q21-q22 7153 126430 Hs.156346 NM_001067 TPX2 chr20q11.2 22974 605917 Hs.244580 NM_012112 TRIM29 chr11q22-q23 23650 Hs.504115 NM_012101, NM_058193 TSPAN-1 chr1p34.1 10103 Hs.38972 NM_005727 VAV3 chr1p13.3 10451 605541 Hs.267659 NM_006113

The terms “MapLocation, LocusLink, Unigene and OMIM” relate to databases in which the respective proteins are listed under the given access number. These databases can be accessed over the NCBI server.

Out of these, preferred genes are the following:

TABLE 2 Preferred genes that can be used to discriminate ESR1 positive tumors from ESR1 negative tumors Gene RefSeq Symbol Map Location LocusLi OMIM UniGene Transcript ALCAM chr3q13.1 214 601662 Hs.150693 NM_001627 ASPN chr9q22 54829 608135 Hs.435655 NM_017680 BCL2 chr18q21.33|18q21.3 596 151430 Hs.150749 NM_000633, NM_000657 CCND1 chr11q13 595 168461 Hs.523852 NM_053056 CDC2 chr10q21.1 983 116940 Hs.334562 NM_001786, NM_033379 CEACAM6 chr19q13.2 4680 163980 Hs.466814 NM_002483 CELSR1 chr22q13.3 9620 604523 Hs.252387 NM_014246 CHI3L1 chr1q32.1 1116 601525 Hs.382202 NM_001276 COL4A5 chrXq22 1287 303630 Hs.369089 NM_000495, NM_033380, NM_033381 CPE chr4q32.3 1363 114855 Hs.75360 NM_001873 CRAT chr9q34.1 1384 600184 Hs.12068 NM_000755, NM_004003, NM_144782 CXCL9 CXCL10 chr4q21 3627 147310 Hs.413924 NM_001565 DNAJC12 chr10q22.1 56521 606060 Hs.260720 NM_021800, NM_201262 FLJ20152 chr5p15.1 54463 Hs.481704 NM_019000 FOS chr14q24.3 2353 164810 Hs.25647 NM_005252 ITPR1 chr3p26-p25 3708 147265 Hs.374613 NM_002222 JMJD2B chr19p13.3 23030 Hs.371013 NM_015015 KIF5C chr2q23.1 3800 604593 Hs.435557 XM_377774 KRT23 chr17q21.2 25984 606194 Hs.9029 NM_015515, NM_173213 KRT5 chr12q12-q13 3852 148040 Hs.433845 NM_000424 KRT6B chr12q12-q13 3854 148042 Hs.524438 NM_005555 LOC492304 chr11p15.5 3481 147470 Hs.523414 NM_001007139 MAPT chr17q21.1 4137 157140 Hs.101174 NM_005910, NM_016834, NM_016835, NM_016841 MAST4 chr5q12.3 23227 Hs.133539 XM_291141 MLPH chr2q37.3 79083 606526 Hs.102406 NM_024101 MMP7 chr11q21-q22 4316 178990 Hs.2256 NM_002423 PHGDH chr1p12 26227 606879 Hs.487296 NM_006623 PROM1 chr4p15.32 8842 604365 Hs.479220 NM_006017 RARRES1 chr3q25.32 5918 605090 Hs.131269 NM_002888, NM_206963 S100A8 chr1q21 6279 123885 Hs.416073 NM_002964 SCUBE2 chr11p15.3 57758 Hs.523468 NM_020974 SLC7A5 chr16q24.3 8140 600182 Hs.513797 NM_003486 SLPI chr20q12 6590 107285 Hs.517070 NM_003064 SOCS2 chr12q 8835 605117 Hs.485572 NM_003877 SOD2 chr6q25.3 6648 147460 Hs.487046 NM_000636 STC2 chr5q35.1 8614 603665 Hs.233160 NM_003714 TFF1 chr21q22.3 7031 113710 Hs.162807 NM_003225 TOP2A chr17q21-q22 7153 126430 Hs.156346 NM_001067 TRIM29 chr11q22-q23 23650 Hs.504115 NM_012101, NM_058193 TSPAN1 chr1p34.1 10103 Hs.38972 NM_005727

The applicants have analysed these genes and were able to assign the said genes to given biological motifs which are correlated with, and are thus predictive for, subgroups of Estrogen receptor (ESR) negative tumors. By way of illustration and not by limitation these motifs may be selected from the group comprising at least

-   -   extracellular matrix degradation (Table 3),     -   growth factor signaling (Table 4),     -   immune cell infiltration (Table 5) and/or     -   basal markers (Table 6).

Extracellular Matrix degradation is frequently caused by Matrix Metalloproteinases. For this reason, most preferred genes are part of the Matrix Metalloproteinase gene family, and the Keratin gene family, which both tend to exhibit bimodal distribution of expression values. Such genes are, for example

-   -   Matrix Metallo Proteinases (MMP), particularly MMP1, MMP3, MMP7,         MMP9, MMP11 and MMP12, most preferred MMP7

TABLE 3 Preferred genes related genes related to extracellular matrix degradation Gene RefSeq Symbol MapLocation LocusLink OMIM UniGene Transcript MMP1 chr11q22.3 120353 Hs.83169 MMP3 chr 11q22.3 185250 Hs.375129 MMP7 chr 11q21-q22 178990 Hs.2256 MMP9 chr 20q11.2- 120361 Hs.297413 q13.1 MMP11 chr 22q11.2- 185261 Hs.143751 q11.23 MMP12 chr 11q22.3 601046 Hs.1695 Hs.645661

Genes related to growth factor signalling may for example encode for hormone receptors, growth factor receptors, growth factor ligands, inhibitors and the like. Such genes comprise, for example, genes encoding a receptor from the ErbB-family, or a gene correlated with the Progesterone receptor (PGR) status in the said sample.

TABLE 4 Preferred genes related related to growth factor signalling Gene Map RefSeq Symbol Location Entrez LocusLink OMIM UniGene Transcript PGR chr11q22- 607311 Hs.368072 q23 ESR chr6q25.1 133430 Hs.208124 EGFR/ErbB1 chr7p12 131550 Hs.488293 VEGFR chr4q11- 191306 Hs.479756 q12 ErbB2/ chr17q11.2- 164870 Hs.446352 Her-2/neu q12; 17q21.1 ErbB4 chr2q33.3- 600543 Hs.390729 q34 C-Kit chr 4q11- 164920 Hs.479754 q12 PDGFRA chr 4q11- 173490 Hs.74615 q13 PDGFRB chr 5q31- 173410 Hs.509067 q32 PDGFRC chr 4q32 608452 Hs.570855 C-MET chr 7q31 164860 Hs.132966

Genes related to immune cell infiltration may be selected from the following table (listing is not exclusive):

TABLE 5 Preferred genes related to immune cell infiltration Gene Map Locus Symbol Location Entrez Link OMIM UniGene RefSeq CD79A chr19q13.2 NM_001783 973 112205 Hs.79630 NM_001783, NM_021601 CD79B chr17q23 NM_000626 974 147245 Hs.89575 NM_000626, NM_021602 CD83 chr6p23 NM_004233 9308 604534 Hs.484703 NM_004233 IGBP1 chrXq13.1- NM_001551 3476 300139 Hs.496267 NM_001551 q13.3 IGH@ chr14q32.33 S65761 3492 Hs.510635 IGH@, chr14q32.33 U80164 IGHG1 IGH@, chr14q32.33 M87789 3502 147120 Hs.525646 IGHG1, IGHG2, IGHM IGH@, chr14q32.33, BG340548 283650 Hs.366 —, IGHG1, chr16p11.2 XM_372632 IGHG2, IGHM, LOC390714, MGC27165 IGHA2, chr14q32.33 S55735 283650 Hs.366 MGC27165 IGHD chr14q32.33 AI858004 3495 147170 Hs.439852 IGHD chr14q32.33 AJ275469 Hs.525874 IGHD chr14q32.33 BG340670 Hs.448957 IGHD chr14q32.33 AW134608 3495 147170 Hs.439852 IGHD, IGHG1, chr14q32.33 M21388 Hs.112610 IGHM, MGC27165 IGHG1 chr14q32.33 M24668 Hs.531234 IGHG1 chr14q32.33 L23519 Hs.449011 IGHG1 chr14q32.33 L14454 3507 147020 Hs.525647 IGHG1 chr14q32.33 L14455 Hs.497707 IGHG1 chr14q32.33 L14456 Hs.497707 IGHG1 chr14q32.33 AJ225092 IGHG1 chr14q32.33 X58397 Hs.532509 IGHG1 chr14q32.33 AJ275397 IGHG1 chr14q32.33 U92706 IGHG1 chr14q32.33 S74639 Hs.497707 IGHG1, chr14q32.33 AJ275408 IGHG3 IGHG1, IGHM chr14q32.33 U80139 IGHG1, chr14q32.33 AJ239383 283650 Hs.366 IGHM, MGC27165 IGHG1, chr14q32.33, M87268 Hs.448957 —, LOC390714 chr16p11.2 XM_372632 IGHG1, chr14q32.33, AB035175 —, LOC390714 chr16p11.2 XM_372632 IGHM chr14q32.33 BC001872 3495 147170 Hs.439852 IGHM chr14q32.33 M24669 3495 147170 Hs.4398502 IGHM chr14q32.33 L23518 3495 147170 Hs.439852 IGHM chr14q32.33 X17115 3495 147170 Hs.439852 IGHM chr14q32.33 BF002659 3495 147170 Hs.439852 IGHMBP2 chr11q13.2- L14754 3508 600502 Hs.503048 NM_002180 q13.4 IGHMBP2 chr11q13.2- AF052128 3508 600502 Hs.503048 NM_002180 q13.4 IGJ chr4q21 AV733266 3512 147790 Hs.381568 NM_144646 IGKC chr2p12 X72475 Hs.512130 IGKC chr2p12 BC005332 3514 147200 Hs.449621 IGKC chr2p12 M63438 3514 147200 Hs.449621 IGKV1D-13 chr2p12 AW408194 28902 Hs.390427 IGL@ chr22q11.1- X93006 Hs.449598 q11.2 IGL@, IGLC2 chr22q11.1- X57812 28831, Hs.449585 q11.2, 3535, chr22q11.2 3538 IGL@, IGLC2 chr22q11.1- AA680302 3546 147240 Hs.449587 q11.2, chr22q11.2 IGL@, IGLC2 chr22q11.1- AV698647 Hs.458262 q11.2, chr22q11.2 IGLC2 chr22q11.2 M87790 Hs.458262 IGLC2 chr22q11.2 H53689 Hs.449582 IGLC2 chr22q11.2 AF043586 28831, Hs.449585 3535, 3538 IGLC2 chr22q11.2 D87021 96610 Hs.449601 IGLC2 chr22q11.2 AJ249377 28831 Hs.517455 IGLC2, IGLJ3 chr22q11.1- AF047245 Hs.537013 q11.2, chr22q11.2 IGLC2, IGLJ3 chr22q11.1- AF234254 28831 Hs.517453 q11.2, chr22q11.2 IGLJ3 chr22q11.1- AB001733 28831 Hs.517453 q11.2 IGLJ3 chr22q11.1- AB014341 28831 Hs.517453 q11.2 IGLL1 chr22q11.23 NM_020070 3543 146770 Hs.348935 NM_020070, NM_152855 IGLL1, chr22q11.23 AL022324 3543 146770 Hs.348935 NM_020070, LOC91316 NM_152855, XM_498877 IGLV6-57 chr22q11.2 AI952772 3546 147240 Hs.449587 IGSF1 chrXq25 NM_001555 3547 300137 Hs.22111 NM_001555, NM_205833 IGSF2 chr1p13 NM_004258 9398 604516 Hs.74115 NM_004258 IGSF3 chr1p13 AB007935 3321 603491 Hs.171057 NM_001007237, NM_001542 IGSF4 chr11q23.2 NM_014333 23705 605686 Hs.370510 NM_014333 IGSF4 chr11q23.2 AL519710 23705 605686 Hs.370510 NM_014333 IGSF4 chr11q23.2 AF132811 23705 605686 Hs.370510 NM_014333 IGSF4B chr1q21.2- AF062733 57863 Hs.365689 NM_021189 q22 IGSF4B chr1q21.2- AI564838 57863 Hs.365689 NM_021189 q22 IGSF4B chr1q21.2- AL050219 57863 Hs.365689 NM_021189 q22 IGSF4B chr1q21.2- AL050219 57863 Hs.365689 NM_021189 q22 IGSF4B chr1q21.2- AI951798, 57863 Hs.365689 NM_021189 q22 AU129642 IGSF4C chr19q13.31 AC005525 199731 Hs.370984 NM_145296 IGSF4C chr19q13.31 AC005525 199731 Hs.370984 NM_145296 IGSF4C chr19q13.31 AW204383 199731 Hs.370984 NM_145296 IGSF6 chr16p12-p13 NM_005849 10261 606222 Hs.530902 NM_005849 ILT10 chr19q13.4 NM_024317 79166 Hs.202680 NM_024317 ILT7 chr19q13.4 AF041261 23547 607517 Hs.406708 NM_012276 ISLR chr15q23-q24 NM_005545 3671 602059 Hs.513022 NM_005545, NM_201526 KIR2DL1 chr19q13.4 U24078 3802 604936 Hs.512572 NM_014218 KIR2DL2 chr19q13.4 L76669 3812 604947 Hs.380156 NM_014219 KIR2DL3 chr19q13.4 AF022048 3804 604938 Hs.512573 NM_014511, NM_015868 KIR2DL4 chr19q13.4 NM_002255 3805 604945 Hs.166085 NM_002255 KIR2DL4 chr19q13.4 AF276292 3805 604945 Hs.166085 NM_002255 KIR2DL4 chr19q13.4 AF002256 3805 604945 Hs.166085 NM_002255 KIR2DL5 chr19p13.3 AF217487 115653, Hs.278457 NM_020535 3811 KIR2DL5, chr19p13.3, AJ000190 115653, Hs.278457 NM_006737, KIR3DL2, chr19q13.4, 3811 NM_020535, KIR3DL3 chr19q13.42 NM_153443 KIR2DS1 chr19q13.4 NM_014512 3805 604945 Hs.166085 NM_014512 KIR2DS2 chr19q13.4 L76668 3812 604947 Hs.380156 NM_012312 KIR2DS3 chr19q13.4 NM_012313 3812 604947 Hs.380156 NM_012313 KIR2DS4 chr19q13.4 AF135564 3806 604952 Hs.512574 NM_012314 NM_178228 KIR2DS5 chr19q13.4 NM_014513 3812 604947 Hs.380156 NM_014513 KIR3DL1 chr19q13.4 AF262973 3812 604947 Hs.380156 NM_013289 KIR3DL2 chr19q13.4 L76666 3812 604947 Hs.380156 NM_006737 KIR3DL2 chr19q13.4 NM_006737 3812 604947 Hs.380156 NM_006737 KIR3DL2 chr19q13.4 AF263617 3812 604947 Hs.380156 NM_006737 KIR3DL2 chr19q13.4 X93596 3812 604947 Hs.380156 NM_006737 KIR3DL3 chr19q13.42 AC006293 3804 604938 Hs.512573 NM_153443 LILRA1 chr19q13.4 NM_006863 10859, Hs.534393 NM_006863 11024 LILRA1 chr19q13.4 AF025529 10859, Hs.534393 NM_006863 11024 LILRA2 chr19q13.4 NM_006866 11027 604812 Hs.534394 NM_006866 LILRA2 chr19q13.4 U82278 11027 604812 Hs.534394 NM_006866 LILRA2 chr19q13.4 U82276 11027 604812 Hs.534394 NM_006866 LILRA2 chr19q13.4 U82277 11027 604812 Hs.534394 NM_006866 LILRA3 chr19q13.4 NM_006865 11026 604818 Hs.113277 NM_006865 LILRB1 chr19q13.4 NM_006669 10859 604811 Hs.149924 NM_006669 LILRB1 chr19q13.4 AF009007 10859 604811 Hs.149924 NM_006669 LILRB2 chr19q13.4 NM_005874 10990 604814 Hs.306230 NM_005874 LILRB2, chr19q13.4 AF004231 10990 604814 Hs.306230 NM_005874 LILRB6 NM_024318 LILRB3 chr19q13.4 AF009635 10288, Hs.515601 NM_006864 11025, 79168 LILRB3 chr19q13.4 AF009634 10288, Hs.515601 NM_006864 11025, 79168 LILRB3 chr19q13.4 AF009643 10288, Hs.515601 NM_006864 11025, 79168 LILRB3 chr19q13.4 AF009644 10288, Hs.515601 NM_006864 11025, 79168 LILRB4 chr19q13.4 U82979 11006 604821 Hs.67846 NM_006847 LILRB5 chr19q13.4 NM_006840 10990 604814 Hs.306230 NM_006840 LILRB6 chr19q13.4 NM_024318 10288, Hs.515601 NM_024318 11025, 79168 LOC440361 chr16p11.2 AJ275383 XM_496145 LOC91316 chr22q11.23 AA398569 91316 Hs.407693 XM_498877 LOC91316 chr22q11.23 AU158566 91316 Hs.407693 XM_498877 LOC91316 chr22q11.23 AK025313 XM_498877 LOC91316 chr22q11.23 L02326 XM_498877 LRIG1 chr3p14 AB050468 26018 608868 Hs.518055 NM_015541 LRIG2 chr1p13.1 NM_014813 9860 608869 Hs.448972 NM_014813 PIGR chr1q31-q41 NM_002644 5284 173880 Hs.497589 NM_002644 SEMA3A chr7p12.1 NM_006080 10371 603961 Hs.252451 NM_006080 SEMA3B chr3p21.3 NM_004636 7869 601281 Hs.82222 NM_001005914, NM_004636 SEMA3C chr7q21-q31 AI962897 10512 602645 Hs.269109 NM_006379 SEMA3C chr7q21-q31 NM_006379 10512 602645 Hs.269109 NM_006379 SEMA3D chr7q21.11 AA343027 223117 Hs.201340 NM_152754 SEMA3D chr7q21.11 AU145680 223117 Hs.201340 NM_152754 SEMA3F chr3p21.3 U38276 6405 601124 Hs.32981 NM_004186 SEMA3F chr3p21.3 NM_004186 6405 601124 Hs.32981 NM_004186 SEMA3F chr3p21.3 U38276 6405 601124 Hs.32981 NM_004186 SEMA4A chr1q22 NM_022367 64218 607292 Hs.408846 NM_022367 SEMA4C chr2q11.2 AI949392 54910 604462 Hs.516220 NM_017789 SEMA4C chr2q11.2 NM_017789 54910 604462 Hs.516220 NM_017789 SEMA4D chr9q22-q31 NM_006378 10507 601866 Hs.511748 NM_006378 SEMA4F chr2p13.1 NM_004263 10505 603706 Hs.25887 NM_004263 SEMA4F chr2p13.1 AL136552 10505 603706 Hs.25887 NM_004263 SEMA4G chr10q24.32 NM_017893 57715 Hs.444359 NM_017893 SEMA7A chr15q22.3- AF071542 8482 607961 Hs.24640 NM_003612 q23 TCF3 chr19p13.3 AA768906, 6929 147141 Hs.371282 NM_003200 M31523 TCF3 chr19p13.3 AI655986, 6929 147141 Hs.371282 NM_003200 M31523 TCF3 chr19p13.3 M31523 6929 147141 Hs.371282 NM_003200 TCF3 chr19p13.3 M31222 6929 147141 Hs.371282 NM_003200 TCF3 chr19p13.3 BE962186 6929 147141 Hs.371282 NM_003200 TCF3 chr19p13.3 AW062341, 6929 147141 Hs.371282 NM_003200 BG393795 TCF3 chr19p13.3 X52078 6929 147141 Hs.371282 NM_003200 TCF3 chr19p13.3 AL117663 6929 147141 Hs.371282 NM_003200 TIE1 chr1p34-p33 NM_005424 7075 600222 Hs.78824 NM_005424 TTID chr5q31 NM_006790 9499 604103 Hs.84665 NM_006790 VSIG4 chrXq12- NM_007268 11326 300353 Hs.8904 NM_007268 q13.3 CXCL9 CXCL10 chr4q21 147310 Hs.413924 NM_001565 IGHM chr14q32.33 147020 Hs.510635 MMP9 chr20q11.2- 120361 Hs.297413 q13.1

Genes related to basal markers (the term “basal markers” is derived from the appearance of the respective cells, which is similar to basal cells) may be selected from the following table (listing is not exclusive):

TABLE 6 Preferred genes related to basal markers Gene Locus RefSeq Symbol Map Location Link OMIM UniGene Transcript KRT5 chr12q12-q13 148040 Hs.694210 Hs.694210 KRT6A chr12q12-q13 148041 Hs.433845 KRT6B chr12q12-q13 148042 Hs.433845 KRT14 chr17q12-q21 148066 Hs.654380 KRT23 chr17q21.2 606194 Hs.9029 KRT17 chr17q12-q21 148069 Hs.2785 MLPH chr2q37.3 79083 606526 Hs.102406 NM_024101

Out of these, most preferred genes are the following:

TABLE 7a Preferred genes in the context of the present invention Gene Symbol Biological motif ERBB2/ growth factor signallling Her-2/neu MMP7 extracellular matrix degradation MMP1 extracellular matrix degradation PGR growth factor signallling ESR1 growth factor signallling MLPH extracellular matrix degradation/basal marker IGHM immune cell infiltration C-Kit growth factor signalling C-MET growth factor signalling EGFR growth factor signalling

Out of these, MMP1, MLPH, ESR1 and Her-2/neu are subject of a most preferred embodiment of the invention.

Furthermore, it is preferred that at least one mode of treatment for which prediction is sought is a neoadjuvant chemotherapy and/or targeted therapy. These two types of therapy are particularly promising in ESR negative (ESR−) tumors which are not susceptible to endocrine treatment with, for example, tamoxifen.

The terms “neoadjuvant therapy”, “chemotherapy” and “targeted therapy” have been defined above.

Said chemotherapy may comprise the administration of at least one agent selected from the group consisting of Cyclophosphamid (Endoxan®, Cyclostin®). Adriamycin (Doxorubicin) (Adriblastin®), BCNU (Carmustin) (Carmubris®), Busulfan (Myleran®), Bleomycin (Bleomycin®), Carboplatin (Carboplat®), Chlorambucil (Leukeran®), Cis-Platin (Cisplatin®), Platinex (Platiblastin®), Dacarbazin (DTIC®; Detimedac®), Docetaxel (Taxotere®), Epirubicin (Farmorubicin®), Etoposid (Vepesid®), 5-Fluorouracil (Fluroblastin®, Fluorouracil®), Gemcitabin (Gemzar®), Ifosfamid (Holoxan®), Interferon alpha (Roferon®), Irinotecan (CPT 11, Campto®), Melphalan (Alkeran®), Methotrexat (Methotrexat®, Farmitrexat®), Mitomycin C (Mitomycin®), Mitoxantron (Novantron®), Oxaliplatin (Eloxatine®), Paclitaxel (Taxol®), Prednimustin (Sterecyt®), Procarbazin (Natulan®), Pemetrexed (Alimta®), Ralitrexed (Tomudex®), Topotecan (Hycantin®), Trofosfamid (Ixoten®), Vinblastin (Velbe®), Vincristin (Vincristin®), Vindesin (Eldisine®) and/or Vinorelbin (Navelbine®).

In particularly preferred embodiments, the following agents and equitoxic modifications thereof are used alone or in combination:

-   -   Taxanes (e.g. Docetaxel, Paclitaxel)     -   Anthracyclins (e.g. Doxorubicine, Epirubicine, Daunorubicin,         Mitoxanthrone, Idarubicin or modifications thereof as e.g.         pegylated anthracyclins)     -   Cyclophosphamide     -   Tubulin modifying agents (e.g. vinorelbine)     -   5′FU based regimen (including Capecitabine)     -   Antibody based regimen (e.g. Avastin®, Erbitux®, Herceptin®)     -   Small molecule inhibitors (e.g. Tykerb®, Tarceva®, Iressa®,         Sutent®, Nexavar®)

Recent studies by the inventors showed furthermore that an overexpression of MMP1 and/or MLPH is frequently correlated with irregularities in the expression of the breast cancer gene BRCA1. BRCA1 (breast cancer 1, early onset) belongs to a class of genes known as tumor suppressors, which maintain genomic integrity to prevent uncontrolled proliferation. The multifactorial BRCA1 protein product is involved in DNA damage repair, ubiquitination, transcriptional regulation as well as other functions. Genetic variations leading to a BRCA1 deficiency have been implicated in a number of hereditary cancers, namely breast, ovarian and prostate, as an important DNA repair system is lost which otherwise would prevent the accumulation of mutations fostering tumor genesis.

Genetic variations of BRCA1 comprise, for example, (i) an altered methylation pattern, (ii) a mutation in the gene (i.e. SNP or gene rearrangements), or (iii) an alteration of the respective promoter.

BRCA1 deficient tumors are known to be quickly growing tumors which are comparatively resistant against chemotherapy. A novel treatment for these tumors is inhibitors of Poly (ADP-ribose) polymerase 1 (PARP1). PARP1 plays a role in repair of single-stranded DNA (ssDNA) breaks. In the absence of PARP1, when these breaks are encountered during DNA replication, the replication fork stalls and double-strand DNA (dsDNA) breaks accumulate. These dsDNA breaks are repaired via homologous recombination (HR) repair. If the HR pathway is functioning, PARP1 deficient mutants do not show an unhealthy phenotype. However, BRCA1 is necessary for the HR pathway to work properly. Therefore, cells which are deficient in BRCA1 are highly sensitive to PARP1 inhibition or knock-down, resulting in cell death by apoptosis, in stark contrast to cells with at least one functionally intact copy of BRCA1.

This means that BRCA1 deficient mutants are likely to become prone to apoptosis in case they are also deficient for PARP1, or PARP1 is inhibited by a respective drug, i.e. a PARP1 inhibitor (see above); preferably if the latter is combined with chemotherapy, e.g. taxane administration. This means, in turn, that PARP1 inhibition therapy is a promising treatment for BRCA1 deficient tumors.

Current tests for BRCA1 deficiencies, as for example performed within clinical trials to test the efficacy of KU-0059436 (PARP1 inhibitor manufactured by Astra Zeneca), comprise only those deficiencies caused by mutation of the BRCA1 gene (i.e. variant (ii)), as these tests perform sequence analysis or use sequence specific probes. BRCA1 deficiencies due to altered methylation patterns, or an alteration of the respective promoter, are not detected by these tests.

Furthermore, direct determination of the expression level of BRCA1 is complex, as the median expression level of BRCA1 is downregulated by approximately 2 fold, which is in the range of assay variabilities for some gene expression determination methods (e.g. RT-PCR), and is highly dependent on the share of tumor cells in the respective sample.

In contrast thereto, the inventors found that simultaneous detection of MMP7 and/or MLPH reveals as well the latter variants discussed above (i.e. variant (i) and (iii), and will thus help to provide adequate treatment for those patients which have a BRCA1 deficiency that is not caused by mutation of the BRCA1 gene itself. The inventors estimate that, by the said simultaneous detection of MMP7 and/or MLPH, between 2 to 5 times more BRCA1 deficient tumors can be detected than with the current tests, which means that up to 5 times more patients can be provided with adequate PARP1 inhibition treatment.

Interestingly, the said correlation between irregularities in BRCA1 expression and the gene expression level of other genes is not only valid for MMP7 and MLPH, but also for MMP1, ESR1, PGR, Her-2/neu, IGHM, C-Kit, C-MET and EGFR, and other genes identified in this application.

Moreover, the inventors have demonstrated that MMP7 positive tumors were frequently found to have decreased expression of RB1 (Retinoblastoma 1), i.e. there seems to be a correlation between MMP7 overexpression and RB1 deficiency. RB1 is not only a negative regulator of the cell cycle (indeed, it has been the first tumor suppressor gene identified), but also involved in the stabilization of constitutive chromatin.

Again, RB1 deficient tumors are particularly sensitive towards intensified chemotherapy and also inclusion of PARP1 inhibitors, namely for the same reasons as mentioned in the context of BRCA1. This means that, for example, PARP1 inhibition and addition of taxanes is beneficial in these tumors, which otherwise have a poor outcome.

As for BRCA1, direct determination of the expression level of RB1 is complex, as the median expression level of RB1 is downregulated by approximately 2 fold, which is in the range of assay variabilities for some gene expression determination methods (e.g. RT-PCR), and is highly dependent on the share of tumor cells in the respective sample.

Again, it is thus beneficial to measure the gene expression of a gene correlated with RB1 irregularities. Interestingly, the said correlation between irregularities in RB1 expression and the gene expression level of other genes is not only valid for MMP7 and MLPH, but also for MMP1, ESR1, PGR, Her-2/neu, IGHM, C-Kit, C-MET and EGFR, and other genes identified in this application.

The above phenomena apply as well to the CCND1 gene (Cyclin D1 (PRAD1). The CCND1 protein contributes to the progression of the cell cycle in the G1/S checkpoint. CCND1 overexpression (for instance as a consequence of CCND1 amplification) might result in loss of control over genetic damage at this point and in an accumulation of chromosomal aberrations.

The inventors found, during their studies related to this invention, that the detection of RB1, BRCA1 and/or CCND1 irregularities and/or deficiencies in basal type tumors, as identified by e.g. MMP7 and/or MLPH expression levels, renders such tumors particularly sensitive to defined therapeutic interventions. The said genes are listed in the following table:

TABLE 7b Negatively correleated/ Gene Map Locus RefSeq coexpressed Symbol Location Link OMIM UniGene Transcript with RB1 13q14.2 180200 Hs.408528 MMP7/MLPH BRCA1 17q21 113705 Hs.194143 MMP7/MLPH CCND1 11q13 168461 Hs.523852 MMP7/MLPH

In a preferred embodiment, it is thus provided that the mode of treatment for which prediction is sought is a therapy directed to the inhibition of homologous recombination repair. This is, for example, being done be determination of MMP7 and/or MLPH, which are reciprocally correlated with RB1, BRCA1 and CCND1. This means that a high expression level of MMP7 and/or MLPH is an indication for a therapy directed to the inhibition of homologous recombination repair. Examples for such therapy are Inhibitors of Poly (ADP-ribose) polymerase 1 (PARP1), like AZD2281 (KU-0059436), FR247304, AG14361, GPI 15427, GPI 16539, caffeine metabolites like 1,7-dimethylxanthine, 3-methylxanthine 1-methylxanthine, theobromine and theophylline, and others.

In yet another preferred embodiment of the present invention, it is provided that the method further comprises the steps of

-   -   e) determining the expression level of at least one gene         correlated and/or coexpressed with a receptor from the         ErbB-family in the said sample, and/or     -   f) determining the expression level of at least one gene         correlated and/or coexpressed with the Progesterone receptor         (PGR) status in the said sample.

In this regard we have found that the expression of Her-2/neu is quite often negatively correlated with EGFR expression. EGFR expression is particularly prominent in tumors exhibiting low expression of Her-2/neu, ESR1 and PGR. However, the exact and robust determination of EGFR expression is critical both on protein and mRNA level. It is particularly difficult to determine a clear cut threshold to reliably discriminate between high and low expressing breast tumors, in part because of a narrow dynamic range of EGFR expression and technical variations due to assay platform or variable tissue composition in independent tumor samples of the same tumor.

In contrast, the determination of MMP7, as an example, is robust and more reliable, as the dynamic range is broader and the data distribution is almost bimodal, enabling to define a biologically and clinically meaningful threshold between high and low expressing tumors.

Moreover, we have found that high expression of MMP7 excludes high expression of Her-2/neu, ESR1 and PGR (=“basal like tumors”). Still not all, but about 50% of the basal like tumors express MMP7. Most preferred is the combination of MMP7 with MLPH, which trends to exhibit bimodal distribution of expression values, while being strongly associated with ESR1 expression.

There is evidence for a correlation between ESR and growth factor receptor pathways, such as the ErbB pathway. The ESR can be phosphorylated at the serine-118 position within AF-1 by the MAPKs ERK1 and ERK2, which are downstream components of the Her-2/neu signalling pathway, the latter being a member of the ErbB receptor family.

Genes related to growth factor signalling may for example encode for growth factor receptors, growth factor ligands, inhibitors and the like.

Genes which meet the above criteria, i.e. that they are correlated and/or coexpressed with a receptor from the ErbB-family or correlated and/or coexpressed with the Progesterone receptor (PGR) status in the said sample are listed in the following table:

TABLE 8a Genes correlated and/or coexpressed with a receptor from the ErbB-family Correleated/ Gene Map Locus coexpressed symbol Location Link Genbank ID Unigene_v133_ID with LASP1 3927 NM_006148.1 75080 ErbB CACNB1 782 NM_000723.1 635 ErbB RPL19RPL19 6143 NM_000981.1 252723 ErbB PPARGBP 5469 Y13467 15589 ErbB CrkRS NM_016507.1 123073 ErbB NEUROD2 4761 AB021742.1 322431 ErbB MLN64 10948 NM_006804.1 77628 ErbB TELETHONIN 8557 NM_003673.1 111110 ErbB PNMT 5409 NM_002686.1 1892 ErbB ERBB2 2064 X03363.1 323910 ErbB GRB7 2886 AB008790.1 86859 ErbB PSMD3 5709 NM_002809.1 9736 ErbB GCSFG 1440 NM_000759.1 2233 ErbB KIAA0130 9862 AI023317 23106 ErbB c-erbA-1 X55005 7067 ErbB NR1D1 9572 X72631 211606 ErbB MLN51 22794 NM_007359.1 83422 ErbB CDC6 990 U77949.1 69563 ErbB RARA U41742.1 5914 ErbB TOP2A 7153 NM_001067.1 156346 ErbB IGFBP4 NM_001552.1 1516 ErbB CCR7 EBI1 CCR7 NM_001838.1 1652 ErbB SMARCE1 6605 NM_003079.1 332848 ErbB KRT10 3858 X14487 99936 ErbB KRT12 NM_000223.1 66739 ErbB hHKa3-II 3884 NM_002279.2 32950 ErbB MLLT6 4302 NM_005937 349196 ErbB ZNF144 7703 XM_008147 184669 ErbB PIP5K2B 8396 NM_138687 432736 ErbB TEM7 57125 NM_020405 125036 ErbB ZNFN1A3 22806 XM_012694 258579 ErbB WIRE 147179 XM_085731 13996 ErbB PSMB3 5691 NM_002795 82793 ErbB MGC9753 93210 NM_033419 91668 ErbB Variant a MGC9753 ErbB Variant c MGC9753 ErbB Variant d MGC9753 ErbB Variant e MGC9753 ErbB Variant g MGC9753 ErbB Variant h MGC9753 ErbB Variant i ORMDL3 94103 AF395708 374824 ErbB MGC15482 84961 NM_032875 194498 ErbB PPP1R1B 84152 NM_032192 286192 ErbB MGC14832 84299 NM_032339 333526 ErbB LOC51242 51242 NM_057555 12101 ErbB FLJ20291 54883 NM_017748 8928 ErbB Pro2521 55876 NM_018530 19054 ErbB Link-GEFII 51195 NM_016339 118562 ErbB CTEN 84951 NM_032865 294022

TABLE 8b Genes correlated and/or coexpressed with the Progesterone receptor (PGR) Correleated/ Gene Map Locus RefSeq coexpressed Symbol Location Link OMIM UniGene Transcript with MAPT chr17q21.1 4137 157140 Hs.101174 NM_005910, PGR NM_016834, NM_016835, NM_016841 MLPH chr2q37.3 79083 606526 Hs.102406 NM_024101 PGR

As part of this invention, it was found that tumors demonstrating elevated expression levels of MMP1 and low and/or undetectable MLPH levels belong to the group of “basal-like tumors” exhibiting low expression of ESR1 and Her-2/neu, but yet having a high risk if not treated by chemotherapy regimen.

Particularly preferred at least one of the receptors the expression level of which is determined is Her-2/neu.

Her-2/neu (also known as ErbB-2, ERBB2) is a member of the ErbB protein family, more commonly known as the epidermal growth factor receptor family. Her-2/neu is notable for its role in the pathogenesis of breast cancer and as a target of treatment. It is a cell membrane surface-bound receptor tyrosine kinase and is normally involved in the signal transduction pathways leading to cell growth and differentiation. Her-2/neu is thought to be an orphan receptor, with none of the EGF family of ligands able to activate it. However, ErbB receptors dimerize on ligand binding, and Her-2/neu is the preferential dimerization partner of other members of the ErbB family. The Her-2/neu gene is a proto-oncogene located at the long arm of human chromosome 17 (17q11.2-q12).

Approximately 25-30 percent of breast cancers, irrespective of whether they are estrogen positive or negative, have an amplification of the Her-2/neu gene or overexpression of its protein product. Overexpression and/or gene amplification of this receptor in breast cancer is associated with increased disease recurrence and worse prognosis.

In another preferred embodiment, it is provided that an additional mode of treatment for which prediction is sought is a treatment related to the signalling pathway of a receptor from the ErbB-family, the PDGFR-family and the C-KIT receptor.

Such treatment may include the administration of

-   -   an agonist of a ligand for receptors from the ErbB-family     -   an antagonist, e.g. an antibody or an antibody fragment, against         said ligand and/or receptor,     -   an antisense nucleic acid inhibiting the expression of a gene         encoding for said ligand and/or receptor,     -   a small molecular drug, and/or     -   a kinase inhibitor specific for the given receptor.

By way of illustration and not by way of restriction said agents may be selected from the group consisting of the agents shown in table 9.

TABLE 9 Target Antagonist Kinase inhibitors Her-2/neu Herceptin Lapatinib (Tykerb) (ErbB-2) (Trastuzumab) GW572016 Pertuzumab AEE-788 CI-1033 PDGFR Gleevec Nexavar Sutent VEGFR Sutent Nexavar Axitinib Pazopanib C-KIT Gleevec receptor Nexavar Sutent

Other potential agents may be selected from the group comprising Cetuximab (tradename Erbitux®, target receptor is EGFR), Matuzumab (EMD7200, target receptor is EGFR), Trastuzumab (tradename Herceptin®, target receptor is Her-2/neu), Pertuzumab (target receptor is Her-2/neu), Bevacizumab (tradename Avastin®, target ligand is VEGFA), 2C3 (target ligand is VEGFA), VEGF-trap (AVE-0005, target ligands are VEGFA and PIGF), IMC-1121B (target receptor is VEGFR2), CDP-791 (target receptor is VEGFR2), Gefitinib (tradename Iressa®, ZD-1839, target receptor is EGFR), Erlotinib (tradename Tarceva®, OSI-774, target receptor is EGFR), EKB-569 (target receptor is EGFR), PKI-166 (target receptor is EGFR),), PKI-166 (target receptor is EGFR), Lapatinib (tradename Tycerb®, target receptor is EGFR and Her-2/neu), GW572016 (target receptors are EGFR and Her-2/neu), AEE-788 (target receptors are EGFR, Her-2/neu and VEGFR-2), CI-1033 (target receptors are EGFR, Her-2/neu and Her4), AZD6474 (target receptors are EGFR and VEGFR-2).

However, other treatments related to the ErbB receptor family signalling pathway which fall under the scope of the present invention comprise the administration of Sorafenib (tradename Nexavar®, BAY 43-9005, target receptors are VEGFR-2, VEGFR-3, c-KIT, PDGFR-B, RET and Raf-Kinase), BAY 57-9352 (target receptor is VEGFR-2), Sunitinib (tradename Sutent®, target receptors are VEGFR-1, VEGFR-2 and PDGFR), AG13925 (target receptors are VEGFR-1 and VEGFR-2), AG013736 (target receptors are VEGFR-1 and VEGFR-2), AZD2171 (target receptors are VEGFR-1 and VEGFR-2), ZD6474 (target receptors are VEGFR-1, VEGFR-2 and VEGFR-3), Vandetenib (ZD 7646), Vatalanib PTK-787/ZK-222584 (target receptors are VEGFR-1 and VEGFR-2), CEP-7055 (target receptors are VEGFR-1, VEGFR-2 and VEGFR-3), CP-547 (target receptors are VEGFR-1 and VEGFR-2), CP-632 (target receptors are VEGFR-1 and VEGFR-2), GW786024 (target receptors are VEGFR-1, VEGFR-2 and VEGFR-3), AMG706 (target receptors are VEGFR-1, VEGFR-2 and VEGFR-3), Imatinib mesylate (tradename Glivec®/Gleevec®, target receptors are bcr-abl and c-KIT), BMS-214662 (target enzyme is Ras farnesyl transferase), CCI-779 (target enzyme is mTOR), RAD0001 (tradename Everolismus®, target enzyme is mTOR), CI-1040 (target enzyme is MEK), SU6668 (target receptors are VEGFR-2, PDGFR-B and FGFR-1), AZD6126, CP547632 (target receptors are VEGFRs), CP868596 GW786034 (target receptors are PDGFRs), ABT-869 (target receptors are VEGFRs and PDGFRs), AEE788 (target receptors are VEGFRs and PDGFRs), AZD0530 (target enzymes are src and abl), and CEP7055.

In this context, other parameters may as well be used and combined in order to predict the therapeutic success for said given mode of treatment. The parameters may be chosen from the group consisting of

-   -   Menopausal status     -   Overall histological state     -   ECOG performance status     -   Serum Her-2/neu level     -   Serum VEGFA level     -   Serum EGFR level     -   Serum MMP status     -   Serum status of complement factors and its fragments (e.g. C3A)     -   LDH serum levels

In yet another preferred embodiment of the present invention, it is provided that said given mode of treatment (a) acts on recruitment of lymphatic vessels, angiogenesis, cell proliferation, cell survival and/or cell motility, and/or b) comprises administration of a chemotherapeutic agent.

Furthermore, it is provided in an another preferred embodiment of the present invention that said given mode of treatment comprises, in addition, administration of small molecule inhibitors, antibody based regimen, anti-proliferation regimen, pro-apoptotic regimen, pro-differentiation regimen, radiation and/or surgical therapy.

It is particularly preferred that, in the method according to the invention, the said expression level is determined by a) a hybridization based method,

-   -   b) a PCR-based method, particularly a quantitative real-time PCR         method,     -   c) determining the protein level,     -   d) a method based on the electrochemical detection of particular         molecules,     -   e) an array based method,     -   f) serial analysis of gene expression (sage), and/or     -   g) a Planar wave guide based method.

The above mentioned methods have in common that they are focused on the detection of nucleic acids, particularly on the detection of mRNA, DNA, PNA, LNA and/or Morpholino. Moreover, these methods provide the option to determine more than two agents at the same time (“multiplexing”). Therefore, not only the expression levels of one gene of interest can be determined, but the expression level of many other genes of interest, like other ligands, receptors, oncogenes or metabolism related genes can be determined in order to better characterize a given cancer or neoplastic disease in a patient.

In another preferred embodiment of the present invention it is provided that said cancer or neoplastic disease is characterized by a negative Estrogen receptor status, a negative progesterone receptor status and/or a negative Her-2/neu receptor status.

Among the different breast cancer subgroups, the group being characterized by negative statuses in all three aspects as mentioned above (also termed “basal tumors”) has the worst prognosis.

A proper detection of this group is thus vital to sort out those patients which will draw any benefit from anti estrogen treatment, anti progestereone treatment and/or anti Her-2/neu treatment.

A different type of therapy, i.e. neoadjuvant chemotherapy, can thus be administered to these patients, in order to avoid side effects of the above mentioned treatments, and to improve therapy prediction.

Furthermore, in a preferred embodiment of the present invention it is provided that said cancer or neoplastic disease is selected from the group consisting of gynaecological cancers including Breast cancer, Ovarian cancer, Cervical cancer, Endometrial cancer, Vulval cancer, and the like.

In yet another preferred embodiment of the present invention it is provided that the expression level of at least one of the said gene/s is determined with RT-PCR (reverse transcriptase polymerase chain reaction) of the ligand and/or receptor related mRNA.

In another preferred embodiment of the present invention, it is provided that the expression level of at least one of the said gene/s is determined in formalin and/or paraffin fixed tissue samples.

In yet another preferred embodiment of the present invention, it is provided that the expression level of at least one of the said gene/s is determined in serum, plasma or whole blood samples.

Routinely, in tumor diagnosis tissue samples are taken as biopsies form a patient and undergo diagnostic procedures. For this purpose, the samples are fixed in formalin and/or paraffin and are then examined with immunohistochemistry methods. The formalin treatment leads to the inactivation of enzymes, as for example the ubiquitous RNA-digesting enzymes (RNAses). For this reason, the mRNA status of the tissue (the so called transcriptome), remains unaffected.

However, the formalin treatment leads to partial depolymerization of the individual mRNA molecules. For this reason, the current doctrine is that formalin fixed tissue samples can not be used for the analysis of the transcriptome of said tissue.

For this reason, it is provided in a preferred embodiment of the present invention that after lysis, the samples are treated with silica-coated magnetic particles and a chaotropic salt, in order to purify the nucleic acids contained in said sample for further determination.

Collaborators of the inventors of the present invention have developed an approach which however allows successful purification of mRNA out of tissue samples fixed in such manner, and which is disclosed, among others, in WO03058649, WO2006136314A1 and DE10201084A1, the content of which is incorporated herein by reference.

Said method comprises the use of magnetic particles coated with silica (SiO₂). The silica layer is closed and tight and is characterized by having an extremely small thickness on the scale of a few nanometers. These particles are produced by an improved method that leads to a product having a closed silica layer and thus entail a highly improved purity. The said method prevents an uncontrolled formation of aggregates and clusters of silicates on the magnetite surface whereby positively influencing the additional cited properties and biological applications. The said magnetic particles exhibit an optimized magnetization and suspension behavior as well as a very advantageous run-off behavior from plastic surfaces. These highly pure magnetic particles coated with silicon dioxide are used for isolating nucleic acids, including DNA and RNA, from cell and tissue samples, the separating out from a sample matrix ensuing by means of magnetic fields. These particles are particularly well-suited for the automatic purification of nucleic acids, mostly from biological body samples for the purpose of detecting them with different amplification methods.

The selective binding of these nucleic acids to the surface of said particles is due to the affinity of negatively charged nucleic acids to silica containing media in the presence of chaotropic salts like guanidinisothiocyanate. Said binding properties are known as the so called “boom principle”. They are described in the European patent EP819696, the content of which is incorporated herein by reference.

The said approach is particularly useful for the purification of mRNA out of formalin and/or paraffin fixed tissue samples. In contrast to most other approaches, which leave very small fragments behind that are not suitable for later determination by PCR and/or hybridization technologies, the said approach creates mRNA fragments which are large enough to allow specific primer hybridization and/or specific probe hybridization. A minimal size of at least 100 bp, more preferably 200 base pairs is needed for specific and robust detection of target gene expression. Moreover it is also necessary to not have too many inter-sample variations with regard to the size of the RNA fragments to guarantee comparability of gene expression results. Other issues of perturbance of expression data by sample preparation problems relate to the contamination level with DNA, which is lower compared to other bead based technologies. This of particular importance, as the inventors have observed, that DNAse treatment is not efficient in approximately 10% of FFPE samples generated by standard procedures and stored at room temperature for some years before cutting and RNA extraction.

The said approach thus allows a highly specific determination of candidate gene expression levels with one of the above introduced methods, particularly with hybridization based methods, PCR based methods and/or array based methods, even in formalin and/or paraffin fixed tissue samples, and is thus extremely beneficial in the context of the present invention, as it allows the use of tissue samples fixed with formalin and paraffin, which are available in tissue banks and connected to clinical databases of sufficient follow-up to allow retrospective analysis.

Furthermore, a kit useful for carrying out one of the said methods is provided, said kit comprising at least

-   -   a) a primer pair and/or a probe each having a sequence         sufficiently complementary to at least one gene according to the         invention, and/or     -   b) an antibody directed against an expression product related to         at least one gene according to the invention.

In yet another embodiment of the invention a method for correlating the clinical outcome of a patient suffering from or at risk of developing a neoplastic disease is provided, said method comprising the steps of:

-   -   a) obtaining a fixed biological sample from said patient;     -   b) determining the expression level of at least one gene of         interest in said sample according to any of the above methods,         and     -   c) correlating the pattern of expression levels determined         in (b) with said patient's data, said data being selected from         the group consisting of etiopathology data, clinical symptoms,         anamnesis data and/or data concerning the therapeutic regimen.

The said method is particularly beneficial for epidemiological studies. These studies profit from the fact that large tissue databases exist comprising paraffin and/or formalin fixed tissue samples together with an extensive documentation of the patient's history, including etiopathology data, clinical symptoms, anamnesis data and/or data concerning the therapeutic regimen.

The said methods allows for large scale studies which comprise the correlation of the clinical outcome of a patient suffering from or at risk of developing a neoplastic disease with a negative or a positive Estrogen receptor status. In order to successfully adopt this approach, the above introduced method for mRNA purification comprising silica coated magnetic beads and chaotropic salts is quite helpful.

Furthermore, the present invention provides a nucleic acid molecule, selected from the group consisting of

-   -   a) the nucleic acid molecule presented as SEQ ID NO:1-28;     -   b) a nucleic acid molecule having a length of 4-80 nucleotides,         preferably 18-30 nucleotides, the sequence of which corresponds         to the sequence of a single stranded fragment of a gene encoding         for a ligand and/or receptor selected from the group consisting         of ESR1, ESR2, PGR, EGFR, Her-2/neu, ERBB3, ERBB4, MLPH, MMP1,         MMP7, MMP9, MMP11, MMP10, MMP13 and immune genes such as IGHM,         IGHG, IGHD, IGLC, IGLJ, IGLL, IGLV;     -   c) a nucleic acid molecule that is a fraction, variant,         homologue, derivative, or fragment of the nucleic acid molecule         presented as SEQ ID NO: 1-28;     -   d) a nucleic acid molecule that is capable of hybridizing to any         of the nucleic acid molecules of a)-c) under stringent         conditions;     -   e) a nucleic acid molecule that is capable of hybridizing to the         complement of any of the nucleic acid molecules of a)-d) under         stringent conditions;     -   f) a nucleic acid molecule that is capable of hybridizing to the         complement of a nucleic acid molecule of e);     -   g) a nucleic acid molecule having a sequence identity of at         least 95% with any of the nucleic acid molecules of a)-f);     -   h) a nucleic acid molecule having a sequence identity of at         least 70% with any of the nucleic acid molecules of a)-f);     -   i) a complement of any of the nucleic acid molecules of a)-h),         or     -   j) a nucleic acid molecule that comprises any nucleic acid         molecule of a)-i).

See table 12 for a sequence listing. These nucleic acids are being used either as primers for a polymerase chain reaction protocol, or as detectable probes for monitoring the said process.

Furthermore it is provided that the said nucleic acid is selected from the group consisting of DNA, RNA, PNA, LNA and/or Morpholino. The nucleic acid may, in a preferred embodiment, be labelled with at least one detectable marker. This feature is applicable particularly for those nucleic acids which serve as detectable probes for monitoring the polymerase chain reaction process.

Such detectable markers may for example comprise at least one label selected from the group consisting of fluorescent molecules, luminescent molecules, radioactive molecules, enzymatic molecules and/or quenching molecules.

In a particularly preferred embodiment, the said detectable probes are labeled with a fluorescent marker at one end and a quencher of fluorescence at the opposite end of the probe. The close proximity of the reporter to the quencher prevents detection of its fluorescence; breakdown of the probe by the 5′ to 3′ exonuclease activity of the taq polymerase breaks the reporter-quencher proximity and thus allows unquenched emission of fluorescence, which can be detected. An increase in the product targeted by the reporter probe at each PCR cycle therefore causes a proportional increase in fluorescence due to the breakdown of the probe and release of the reporter.

In another preferred embodiment of the present invention, a kit of primers and/or detection probes is provided, comprising at least one of the nucleic acids according to the above enumeration and/or their fractions, variants, homologues, derivatives, fragments, complements, hybridizing counterparts, or molecules sharing a sequence identity of at least 70%, preferably 95%.

Said kit may, in another preferred embodiment, comprise at least one of the nucleic acid molecules presented as SEQ ID NO: 1-28, and/or their fractions, variants, homologues, derivatives, fragments, complements, hybridizing counterparts, or molecules sharing a sequence identity of at least 70%, preferably 95%, for the detection of at least one gene of interest.

Furthermore, the use of a nucleic acid according as recited above, or of a kit as recited above for the prediction of a clinical response of a patient suffering from or at risk of developing a neoplastic disease towards a given mode of treatment.

Disclaimer

To provide a comprehensive disclosure without unduly lengthening the specification, the applicant hereby incorporates by reference each of the patents and patent applications referenced above.

The particular combinations of elements and features in the above detailed embodiments are exemplary only; the interchanging and substitution of these teachings with other teachings in this and the patents/applications incorporated by reference are also expressly contemplated. As those skilled in the art will recognize, variations, modifications, and other implementations of what is described herein can occur to those of ordinary skill in the art without departing from the spirit and the scope of the invention as claimed. Accordingly, the foregoing description is by way of example only and is not intended as limiting. The invention's scope is defined in the following claims and the equivalents thereto. Furthermore, reference signs used in the description and claims do not limit the scope of the invention as claimed.

BRIEF DESCRIPTION OF THE EXAMPLES AND DRAWINGS

Additional details, features, characteristics and advantages of the object of the invention are disclosed in the subclaims, and the following description of the respective figures and examples, which, in an exemplary fashion, show preferred embodiments of the present invention. However, these drawings should by no means be understood as to limit the scope of the invention.

Example 1

Core needle biopsy specimen of breast tumors, which had been formalin fixed (FFPE tissues) or were available as fresh tissues were analyzed. Formalin fixed tissues were available from breast cancer patients (≥cT2, NO/N1, MO) receiving neoadjuvant chemotherapy of 4 cycles of epirubicin and cyclophosphamide (90/600 mg/m2) followed by 4 cycles paclitaxel (175 mg/m²). Trastuzumab was administered parallel to paclitaxel therapy on a three weekly dose (6 mg/kg) and continued for 33 weeks after surgery (according to the TECHNO trial) if tumors were IHC positive (e.g DAKO status 3 with intense and continuous membrane staining) or FISH positive (e.g. >2.1 gene copies of Her-2/neu gene per nucleus). Patients with Her-2/neu negative tumors (equally to IHCl+ or FISH negative testing) were not treated with trastuzumab (PREPARE trial). The Her-2/neu status was determined in core-needle biopsies of all patients by immunohistochemistry or FISH analysis at a central reference pathology department. In total 853 Paraffin embedded core needle biopsies were used for analysis. In addition, 86 fresh tissue specimen were used from breast cancer patients ((cT1-4, N0/N1, MO) receiving neoadjuvant chemotherapy of 4 to 6 cycles of epirubicin and cydophosphamide (90/600 mg/m²) 14 days apart. The samples were flash-frozen and analyzed by microarrays.

Analysis of MMP genes (in particular MMP7), MLPH, Keratins (in particular Keratin 5) and genes related to the Immune System such as the immunoglobulin gene family (e.g. IGHM, IGHG, IGHD, IGLC, IGLJ, IGLL, IGLV and the like were informative and did predict response to neoadjuvant chemotherapy.

Combinatorial analysis of genes such as MMP7, Keratin 5, MLPH and IGHM status on the RNA level were possible and meaningful in fresh tissue specimen by commercially available Affymetrix GeneArrays and in FFPE tissues from core needle biopsies despite highly variable tumor contents. Overall there was a good correlation between the different IHC, FlSH and qPGR methods for standard markers such as ESR1 and Her-2/neu, although the tumor cell content of the tissues varied substantially with 46% of the tumors having a tumor cell content of >50% and 16% of the tumors having less than 20% tumor cells (median 40%).

Example 2

The determination of high MMP7 and low MLPH and Her-2/neu expression levels identified a population of breast tumors having a particularly good response to chemotherapy. By this combined analysis we could identify a subpopulation of ESR1 negative tumors that drew benefit from neoadjuvant treatment consisting of an anthracyclin and cyclophosphamid and therefore could be spared from additional regimen (such as Taxol).

Example 3

A group of patients was treated with adjuvant anthracycline-based dose-dense sequential chemotherapy (E-CMF vs. E-T-CMF) in the context of a randomized Phase III study. RNA was isolated from 217 fixed tumor tissue samples employing an experimental method based on magnetic beads from Siemens Medical Solutions Diagnostics, followed by kinetic one-step RT-PCR for mRNA expression analysis. Identification of molecular subtypes was based on 2D hierarchical clustering of four genes. One of these genes (melanophilin, MLPH) is known to be associated with ESR1-positive tumors only.

The hierarchical clustering based on ESR, PGR, Her-2/neu, and MLPH mRNA expression resulted into 6 identifiable groups, i.e.

-   -   1=ESR and PGR positive     -   5=ESR and Her-2/neu positive     -   4=ESR less positive and PGR negative     -   6=Basal Like with some ESR and Her-2/neu activity left     -   2=Her-2/neu positive and ESR negative     -   3=Basal like with lowest ESR and PGR activity

See FIG. 2 for an illustration. Furthermore, two groups (groups 6 and 3) of low (basal-like, 14+18=32 of 217, 15%) and two groups (1 and 5) of high (86 of 217, 40%) mRNA expression were identified.

Patients with basal-like tumors (i.e. groups 6 and 3) were found to have significantly shorter overall survival (p=0.02) compared to the patients with high mRNA expression. No difference was found in terms of disease-free survival (p=0.373) (see FIGS. 3 and 4). Interestingly, survival of basal-like patients appears to reach a plateau after the 5th year, with neither recurrences nor deaths being observed during an additional 4 years of follow-up.

The results of this study confirm that basal-like patients, identified by only four genes among high-risk breast cancer patients, have a poor prognosis. Confirmation studies are currently being performed by evaluating specific basal-like genes.

It is worth mentioning that the above analysis has been carried out

-   -   on the basis of the determination of the expression level of         four genes only (alternatively, genes can be determined which         are coexpressed with any of these genes), and     -   on the basis of Formalin-Fixed Paraffin-Embedded Tissue.

Methods according to the state of the art (as disclosed in Sorlie et al., 2001) require the analysis of more than 500 genes, and the use of fresh tissue. While the first advantage is due to intelligent test design, the later is due to use of the Siemens Proprietary magnetic bead technology (see claim XX and discussion).

Example 4

In order to investigate possible differential EGF and VEGF receptor mRNA expression in the two basal-like subtypes described in Example 3, the following experiment was carried out.

Patients were treated with adjuvant anthracycline-based dose-dense sequential chemotherapy (E-CMF vs. E-T-CMF) in the context of a randomized Phase III study. RNA was isolated from 217 fixed tumor tissue samples, followed by kinetic one-step RT-PCR for mRNA expression analysis of EGFR, VEGFR2 and VEGFR3. Identification of the basal-like subtypes was based on 2D hierarchical clustering.

One of the basal-like subtypes (14 of 217 patients, 6%, group 6 of Example 3) was found to retain some expression of the Her-2/neu, ESR and MLPH genes.

The second basal-like subtype (18 of 217 patients, 8%, group 3 of Example 3) was characterized by low mRNA expression of all four genes. Significantly more patients in group 6 exhibited high VEGFR2 and VEGFR3 mRNA expression compared to group 3 (Fisher's exact test, p=0.026 and p=0.025, respectively).

Patients being thus characterised might therefore receive benefit from anti VEGF-therapy, for example with sunitinib (Sutent), sorafenib (Nexavar), axitinib, and pazopanib.

In contrast, no such difference was observed for EGFR mRNA expression, i.e. both groups featured a relatively high EGFR gene expression. This means that significantly more patients in the two basal-like subtypes exhibited high EGFR mRNA expression compared to a group of non-basal-like patients (86 of 217, 40%) exhibiting high mRNA expression of all four genes (p<0.0001).

The results of this retrospective study suggest that patients from both basal-like subtypes may be candidates for new anti-EGFR agents. However, agents targeting the VEGF receptor family may only be active in the subgroup of basal-like patients retaining some expression of the Her-2, ESR and MLPH genes (group 6).

Example 5

Further analysis revealed that in tumors of group 3 the gene Birc5 (survivin) is highly expressed (no data shown). This gene has the following specification

TABLE 10 Survivin gene Gene Map Locus RefSeq Symbol Location Link OMIM UniGene Transcript BIRC5 chr17q25 603352 Hs.514527

Survivin is a member of inhibitors of apoptosis (IAPB) family, which are upregulated in various malignancies. It has been described that high survivin expression is associated with favorable outcome of some carcinomas after radiation therapy (Freier et al. (2007).

This means that group 3 tumors, while not likely to be affected by anti VEGF therapy, might be susceptible to radiation therapy.

It is worth to be mentioned that a differentiation of the two basal-like subtypes (i.e. groups 3 and 6) has for the first time been described here.

Sor far, basal-like subtype tumors were classified as high-risk breast cancer patients, associated with poor prognosis. The differentiation as described above opens new ways to provide a more specific therapy to the patients affected, i.e. anti VEGF therapy (for group 6) or radiotherapy (for group 3). This has so far not been possible.

FIG. 1

The inventors have further analyzed said genes in breast carcinomas treated with neoadjuvant chemotherapeutic treatments (e.g. EC, EC-T, TAC) to analyze whether these tumors do respond to chemotherapeutic regimen. These analysis were done by Affymetrix array analysis (HG U133A) in fresh tissue biopsies or RT-kPCR analysis in fixed tissue biopsies of high risk breast tumors. It was found that >60% of these tumors do respond to chemotherapeutic regimen by pathological complete response, meaning no tumor is left after chemotherapeutic regimen in the primary tumor site or in the lymphnodes. This reflects a more that 4 fold higher response rate in this subgroup of patients compared to the unstratified cohort which refelected an approximately 15% pCR rate. 50% of all pathological complete responding breast tumors were within this subgroup of patients, which refelected approximately 15% of all patients. Breast tumors exhibiting a pathological complete response after chemotherapeutic treatment exhibit a good prognosis.

In addition, if tumors were further selected on basis of high immune marker expression, such as IGHM expression levels, approximately 90% of the tumors having high MMP7 and low MLPH level exhibited pathological complete response as depicted in FIG. 2.

Hormonal receptor status and Her-2/neu over-expression are important prognostic variables in patients with operable breast cancer. The majority of basal-like tumors are triple-negative for estrogen receptors (ESR), progesterone (PGR) and Her-2/neu receptors. Such tumors are found in approximately 120 of breast cancer patients and have been shown to have a poor prognosis.

FIG. 2

FIG. 2 shows identification of the basal-like subtypes based on 2D hierarchical clustering, as described in Example 3. Green indicates low gene expression, whereas red indicates high gene expression The Molecular classification was based on only four genes (estrogen receptors (ESR), progesterone receptors (PGR), Her-2/neu, and melanophilin (MLPH).

The analysis revealed the following tumor types:

-   -   1=ESR and PGR positive     -   5=ESR and Her-2/neu positive     -   4=ESR less positive and PGR negative     -   6=Basal Like with some ESR and Her-2/neu activity left     -   2=Her-2/neu positive and ESR negative     -   3=Basal like with lowest ESR and PGR activity

The following table gives an overview about the different groups and potential therapeutic approaches:

TABLE 11a Tumor groups classifiable with the method according to the invention, and possible therapies Marker status/ Group expression level Tumor status Therapy approach 1 ESR and PGR ESR positive Endocrine therapy, positive i.e. tamoxifen 5 ESR and Her-2/neu ESR positive Endocrine therapy positive, PGR on a in combination with medium level anti-ErbB therapy (i.e. trastuzumab) 4 ESR on a medium level, PGR negative, Her-2/neu 6 some residual ESR “triple negative”, anti VEGF therapy and Her-2/neu activity Basal like Tumor (i.e. Nexavar); left, PGR negative optionally: new anti-ErbB therapy 2 Her-2/neu positive anti ErbB therapy and ESR negative (i.e. trastuzumab) 3 ESR and PGR almost “triple negative”, anti VEGF therapy zero, some residual Basal like Tumor (i.e. Nexavar); Her-2/neu activity left Birc5 (survivin) optionally: new high anti-ErbB therapy. Radiotherapy due to coexpression of Birc5

Furthermore, as mentioned above, groups 3 and 6 can be further specified with respect to their CCND, BRCA1 and RB1 status, namely by means of detecting the MMP7 and/or MLPH status. This in turn may open up complementary therapeutic approaches:

TABLE 11b Tumor groups classifiable with another method according to the invention, and possible therapies Marker status/ Group expression level Tumor status Therapy approach 3 or 6 MMP7 positive CCND negative inhibition of and/or RB1 negative homologous MLPH positive BRCA1 negative recombination repair (e.g. PARP1 inhibition)

FIGS. 3 and 4

FIGS. 3 and 4 show Kaplan Meyer curves in which, for the different groups determined as above (see Example 3), the overall survival time (OAS) is plotted versus the respective percentage. It is obvious that the basal-like subtypes (groups 6 and 3) have the worst survival rates, and are thus associated with poor prognosis. For this reason, it is vital that the method according to the invention provides a method to detect these subtypes, in order to submit the respective patients to different and/or novel treatments.

Appendix: Primer sequences TABLE 12: Primer sequences and probe sequences used in accordance with the present invention SEQ ID NO: Gene PCR probe Forward primer Reverse primer  1-3 ERBB2 AGGCCAAGTCCGC TCTGGACGTGCCAG CCTGCTCCCTGAGGA Her- AGAAGCCCT TGTGAA CACAT 2/neu  4-6 ERBB2 ACCAGGACCCACC CCAGCCTTCGACAA TGCCGTAGGTGTCCC Her- AGAGCGGG CCTCTATT TTTG 2/neu  7-9 ERBB2 TGATCATGGTCAA CCATCTGCACCATT CGGAATCTTGGCCGA Her- ATGTTGGATGATT GATGTCTAC CATT 2/neu GACTC  9-12 ERBB2 AAGATTCCCCTTC ACGCCCTCAGAAGA TGTGCTGACGCAAGC Her- TTCCTGGGA TTGGAA TACAAC 2/neu 13-15 MLPH CCAGCAGGCAGAG GCAGTGACGGCCTC CTGCAATCCTGGATT AGCGAGGTTTC AGAAG CAATGTC 16-18 MLPH CCAAATGCAGACC TCGAGTGGCTGGGA AGATAGGGCACAGCC CTTCAAGTGAGGC AACTTG ATTGC 19-21 MLPH CGGGCGTCTTCTG CGATGTGGACACCT AGGCATTCCACAGCT AGAGTCAGATCTT CTGATGA GAAATATG TG 22-24 MMP7 CAGTCTAGGGATT GAACGCTGGACGGA GAATGGCCAAGTTCA AACTTCCTGTATG TGGTA TGAGTTG CT 25-28 MMP7 AGTGGGAACAGGC CGGGAGGCATGAGT GGCATTTTTTGTTTC TCAGGACTATCTC GAGCTA TGAGTCATAGA AAGAG

LIST OF REFERENCES

-   Freier et al., Int. J. Cancer Volume 120, Issue 4, Pages 942-946     (2007) -   Faneyte et al., British Journal of Cancer 88, 406-412 (2003) -   Ring et al., Endocr Relat Cancer 11: 643-658 (2004) -   Sorlie et al., PNAS 98(19): 10869-74 (2001) 

What is claimed is:
 1. A method for predicting a clinical response of a patient suffering from or at risk of developing a neoplastic disease towards at least one given mode of treatment, said method comprising the steps of: a) obtaining a biological sample from said patient; b) determining, on a non protein basis, the expression level of at least one gene of interest, said gene being correlated with the Estrogen receptor (ESR) status in the said sample, c) comparing the pattern of expression levels determined in (b) with one or several reference pattern(s) of expression levels; and d) predicting therapeutic success for said given mode of treatment in said patient from the outcome of the comparison in step (c).
 2. The method according to claim 1, characterized in that the at least one gene of interest is correlated with a negative Estrogen receptor status.
 3. The method of claim 1, characterized in that the at least one gene of interest may be assigned to at least one biological motif selected from the group consisting of extracellular matrix degradation, growth factor signaling, immune cell infiltration, and/or basal markers.
 4. The method of claim 1, characterized in that the method further comprises the steps of e) determining the expression level of at least one gene correlated and/or coexpressed with a receptor from the ErbB-family in the said sample, and/or f) determining the expression level of at least one gene correlated and/or coexpressed with the Progesteron receptor (PGR) status in the said sample.
 5. The method according to claim 4, characterized in that the gene of interest the expression level of which is determined is selected from the group comprising Her-2/neu(=ErbB), MMP7, MMP1, PGR, ESR1, MLPH, IGHM, C-Kit, C-MET and/or EGFR.
 6. The method of claim 1, characterized in that at least one mode of treatment for which prediction is sought is a neoadjuvant chemotherapy, a targeted therapy and/or a therapy directed to the inhibition of homologous recombination repair.
 7. The method of claim 1, characterized in that an additional mode of treatment for which prediction is sought is a treatment related to the signalling pathway of a receptor from the ErbB-family.
 8. The method of claim 1, wherein the expression level is determined by a) a hybridization based method, b) a PCR-based method, particularly a quantitative real-time PCR method, c) determining the protein level, d) a method based on the electrochemical detection of particular molecules, e) an array based method, f) serial analysis of gene expression (sage) and/or g) a Planar wave guide based method.
 9. The method of claim 1, characterized in that said cancer or neoplastic disease is characterized by a negative Estrogen receptor status, a negative progesterone receptor status and/or a negative Her-2/neu receptor status.
 10. The method of claim 1, characterized in that said cancer or neoplastic disease is selected from the group consisting of gynaecological cancers including Breast cancer, Ovarian cancer, Cervical cancer, Endometrial cancer, and/or Vulval cancer.
 11. The method of claim 1, characterized in that the expression level of at least one of the said genes is determined with rtPCR (reverse transcriptase polymerase chain reaction) of the gene-related mRNA.
 12. The method of claim 1, characterized in that the expression level of at least one of the said ligands of is determined in formalin and/or paraffin fixed tissue samples.
 13. The method claim 1, wherein, after lysis, the samples are treated with silica-coated magnetic particles and a chaotropic salt, in order to purify the nucleic acids contained in said sample for further determination.
 14. A kit, comprising at least a) a primer pair and/or a probe each having a sequence sufficiently complementary to at least one gene as set forth in any of the aforementioned claims, and/or b) an antibody directed against an expression product related to at least one gene as set forth in any of the aforementioned claims
 15. A method for correlating the clinical outcome of a patient suffering from or at risk of developing a neoplastic disease, said method comprising the steps of: a) obtaining a fixed biological sample from said patient; b) determining the expression level of at least one gene of interest in said sample according to any of the above methods, and c) correlating the pattern of expression levels determined in (b) with said patient's data, said data being selected from the group consisting of etiopathology data, clinical symptoms, anamnesis data and/or data concerning the therapeutic regimen.
 16. A nucleic acid molecule, selected from the group consisting of a) the nucleic acid molecule presented as SEQ ID NO:1-28 b) a nucleic acid molecule having a length of 4-80 nucleotides, preferably 18-30 nucleotides, the sequence of which corresponds to the sequence of a single stranded fragment of a gene encoding for a ligand and/or receptor selected from the group consisting of ESR1, ESR2, PGR, EGFR, Her-2/neu, ERBB3, ERBB4, MLPH, MMP1, MMP7, MMP9, MMP11, MMP10, MMP13 and immune genes such as IGHM, IGHM, IGHG, IGHD, IGLC, IGLJ, IGLL, IGLV; c) a nucleic acid molecule that is a fraction, variant, homologue, derivative, or fragment of the nucleic acid molecule presented as SEQ ID NO: 1-28; d) a nucleic acid molecule that is capable of hybridizing to any of the nucleic acid molecules of a)-c) under stringent conditions; e) a nucleic acid molecule that is capable of hybridizing to the complement of any of the nucleic acid molecules of a)-d) under stringent conditions; f) a nucleic acid molecule that is capable of hybridizing to the complement of a nucleic acid molecule of e) g) a nucleic acid molecule having a sequence identity of at least 95% with any of the nucleic acid molecules of a)-f); h) a nucleic acid molecule having a sequence identity of at least 70% with any of the nucleic acid molecules of a)-f); i) a complement of any of the nucleic acid molecules of a)-h), or j) a nucleic acid molecule that comprises any nucleic acid molecule of a)-i).
 17. The nucleic acid according to claim 16, characterized in that the said nucleic acid is selected from the group consisting of DNA, RNA, PNA, LNA and/or Morpholino.
 18. The nucleic acid of claim 16, characterized in that it is labelled with at least one detectable marker.
 19. A kit of primers and/or detection probes, comprising at least one of the nucleic acids of claim 16 and/or their fractions, variants, homologues, derivatives, fragments, complements, hybridizing counterparts, or molecules sharing a sequence identity of at least 70%, preferably 95%.
 20. The kit according to claim 19, comprising at least one of the nucleic acid molecules presented as SEQ ID NO: 1-28 and/or their fractions, variants, homologues, derivatives, fragments, complements, hybridizing counterparts, or molecules sharing a sequence identity of at least 70%, preferably 95%, for the detection of at least one gene of interest.
 21. (canceled) 